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ORCIDLawrence Carin
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- affiliation: Duke University, Durham, USA
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2020 – today
- 2024
[j125]Hao Zhang
, Yulai Cong, Zhengjue Wang, Lei Zhang, Miaoyun Zhao, Liqun Chen, Shijing Si, Ricardo Henao, Lawrence Carin:
Text Feature Adversarial Learning for Text Generation With Knowledge Transfer From GPT2. IEEE Trans. Neural Networks Learn. Syst. 35(5): 6558-6569 (2024)- [c307]Vinay Kumar Verma, Nikhil Mehta, Kevin J. Liang, Aakansha Mishra, Lawrence Carin:
Meta-Learned Attribute Self-Interaction Network for Continual and Generalized Zero-Shot Learning. WACV 2024: 2709-2719 - [i176]Aaron T. Wang, Ricardo Henao, Lawrence Carin:
Transformer In-Context Learning for Categorical Data. CoRR abs/2405.17248 (2024) - [i175]Xiang Cheng, Lawrence Carin, Suvrit Sra:
Graph Transformers Dream of Electric Flow. CoRR abs/2410.16699 (2024) - 2023
- [j124]Hongteng Xu, Jiachang Liu, Dixin Luo, Lawrence Carin:
Representing Graphs via Gromov-Wasserstein Factorization. IEEE Trans. Pattern Anal. Mach. Intell. 45(1): 999-1016 (2023) - [j123]Dixin Luo, Hongteng Xu, Lawrence Carin:
Differentiable Hierarchical Optimal Transport for Robust Multi-View Learning. IEEE Trans. Pattern Anal. Mach. Intell. 45(6): 7293-7307 (2023) - [j122]Paidamoyo Chapfuwa, Chenyang Tao, Chunyuan Li, Irfan Khan, Karen Chandross, Michael J. Pencina, Lawrence Carin, Ricardo Henao:
Calibration and Uncertainty in Neural Time-to-Event Modeling. IEEE Trans. Neural Networks Learn. Syst. 34(4): 1666-1680 (2023) - [j121]Hao Zhang, Chaojie Wang, Zhengjue Wang, Zhibin Duan, Bo Chen, Mingyuan Zhou, Ricardo Henao, Lawrence Carin:
Learning Hierarchical Document Graphs From Multilevel Sentence Relations. IEEE Trans. Neural Networks Learn. Syst. 34(8): 4273-4285 (2023) - [c306]Vinay Kumar Verma, Nikhil Mehta, Shijing Si, Ricardo Henao, Lawrence Carin:
Pushing the Efficiency Limit Using Structured Sparse Convolutions. WACV 2023: 6492-6502 - [i174]Ke Bai, Guoyin Wang, Jiwei Li, Sunghyun Park, Sungjin Lee, Puyang Xu, Ricardo Henao, Lawrence Carin:
Open World Classification with Adaptive Negative Samples. CoRR abs/2303.05581 (2023) - [i173]Vinay Kumar Verma, Nikhil Mehta, Kevin J. Liang, Aakansha Mishra, Lawrence Carin:
Meta-Learned Attribute Self-Interaction Network for Continual and Generalized Zero-Shot Learning. CoRR abs/2312.01167 (2023) - 2022
- [j120]Weituo Hao, Nikhil Mehta, Kevin J. Liang, Pengyu Cheng, Mostafa El-Khamy, Lawrence Carin:
WAFFLe: Weight Anonymized Factorization for Federated Learning. IEEE Access 10: 49207-49218 (2022) - [j119]Rachel Lea Draelos, Lawrence Carin:
Explainable multiple abnormality classification of chest CT volumes. Artif. Intell. Medicine 132: 102372 (2022) - [j118]Xunlin Zhan, Yuan Li, Xiao Dong, Xiaodan Liang, Zhiting Hu, Lawrence Carin:
elBERto: Self-supervised commonsense learning for question answering. Knowl. Based Syst. 258: 109964 (2022) - [j117]Longxi Zhou, Xianglin Meng, Yuxin Huang, Kai Kang, Juexiao Zhou, Yuetan Chu, Haoyang Li, Dexuan Xie, Jiannan Zhang, Weizhen Yang, Na Bai, Yi Zhao, Mingyan Zhao, Guohua Wang, Lawrence Carin, Xigang Xiao, Kaijiang Yu, Zhaowen Qiu, Xin Gao:
An interpretable deep learning workflow for discovering subvisual abnormalities in CT scans of COVID-19 inpatients and survivors. Nat. Mach. Intell. 4(5): 494-503 (2022) - [c305]Jiachang Liu, Dinghan Shen, Yizhe Zhang, Bill Dolan, Lawrence Carin, Weizhu Chen:
What Makes Good In-Context Examples for GPT-3? DeeLIO@ACL 2022: 100-114 - [c304]Dhanasekar Sundararaman, Vivek Subramanian, Guoyin Wang, Liyan Xu, Lawrence Carin:
Improving Downstream Task Performance by Treating Numbers as Entities. CIKM 2022: 4535-4539 - [c303]Ke Bai, Guoyin Wang, Jiwei Li, Sunghyun Park, Sungjin Lee, Puyang Xu, Ricardo Henao, Lawrence Carin:
Open World Classification with Adaptive Negative Samples. EMNLP 2022: 4378-4392 - [c302]Qitong Gao, Dong Wang, Joshua David Amason, Siyang Yuan, Chenyang Tao, Ricardo Henao, Majda Hadziahmetovic, Lawrence Carin, Miroslav Pajic:
Gradient Importance Learning for Incomplete Observations. ICLR 2022 - [c301]Qing Guo, Junya Chen, Dong Wang, Yuewei Yang, Xinwei Deng, Jing Huang, Lawrence Carin, Fan Li, Chenyang Tao:
Tight Mutual Information Estimation With Contrastive Fenchel-Legendre Optimization. NeurIPS 2022 - [c300]Paidamoyo Chapfuwa, Sherri Rose, Lawrence Carin, Edward Meeds, Ricardo Henao:
Capturing actionable dynamics with structured latent ordinary differential equations. UAI 2022: 286-295 - [c299]Siyang Yuan, Yitong Li, Dong Wang, Ke Bai, Lawrence Carin, David E. Carlson:
Learning to Weight Filter Groups for Robust Classification. WACV 2022: 3321-3330 - [i172]Paidamoyo Chapfuwa, Sherri Rose, Lawrence Carin, Edward Meeds, Ricardo Henao:
Capturing Actionable Dynamics with Structured Latent Ordinary Differential Equations. CoRR abs/2202.12932 (2022) - [i171]Xunlin Zhan, Yuan Li, Xiao Dong, Xiaodan Liang, Zhiting Hu, Lawrence Carin:
elBERto: Self-supervised Commonsense Learning for Question Answering. CoRR abs/2203.09424 (2022) - [i170]Dhanasekar Sundararaman, Vivek Subramanian, Guoyin Wang, Liyan Xu, Lawrence Carin:
Number Entity Recognition. CoRR abs/2205.03559 (2022) - [i169]Ke Bai, Aonan Zhang, Zhizhong Li, Ricardo Henao, Chong Wang, Lawrence Carin:
Collaborative Anomaly Detection. CoRR abs/2209.09923 (2022) - [i168]Dhanasekar Sundararaman, Nikhil Mehta, Lawrence Carin:
Pseudo-OOD training for robust language models. CoRR abs/2210.09132 (2022) - [i167]Vinay Kumar Verma, Nikhil Mehta, Shijing Si, Ricardo Henao, Lawrence Carin:
Pushing the Efficiency Limit Using Structured Sparse Convolutions. CoRR abs/2210.12818 (2022) - 2021
- [j116]David Dov, Shahar Z. Kovalsky, Serge Assaad, Jonathan Cohen, Danielle Elliott Range, Avani A. Pendse, Ricardo Henao, Lawrence Carin:
Weakly supervised instance learning for thyroid malignancy prediction from whole slide cytopathology images. Medical Image Anal. 67: 101814 (2021) - [j115]Rachel Lea Draelos, David Dov, Maciej A. Mazurowski, Joseph Y. Lo, Ricardo Henao, Geoffrey D. Rubin, Lawrence Carin:
Machine-learning-based multiple abnormality prediction with large-scale chest computed tomography volumes. Medical Image Anal. 67: 101857 (2021) - [c298]Hongteng Xu, Dixin Luo, Lawrence Carin, Hongyuan Zha:
Learning Graphons via Structured Gromov-Wasserstein Barycenters. AAAI 2021: 10505-10513 - [c297]Yulai Cong, Miaoyun Zhao, Jianqiao Li, Junya Chen, Lawrence Carin:
GO Hessian for Expectation-Based Objectives. AAAI 2021: 12060-12068 - [c296]Nikhil Mehta, Kevin J. Liang, Vinay Kumar Verma, Lawrence Carin:
Continual Learning using a Bayesian Nonparametric Dictionary of Weight Factors. AISTATS 2021: 100-108 - [c295]Serge Assaad, Shuxi Zeng, Chenyang Tao, Shounak Datta, Nikhil Mehta, Ricardo Henao, Fan Li, Lawrence Carin:
Counterfactual Representation Learning with Balancing Weights. AISTATS 2021: 1972-1980 - [c294]David Dov, Serge Assaad, Shijing Si, Rui Wang, Hongteng Xu, Shahar Ziv Kovalsky, Jonathan Bell, Danielle Elliott Range, Jonathan Cohen, Ricardo Henao, Lawrence Carin:
Affinitention nets: kernel perspective on attention architectures for set classification with applications to medical text and images. CHIL 2021: 14-24 - [c293]Paidamoyo Chapfuwa, Serge Assaad, Shuxi Zeng, Michael J. Pencina, Lawrence Carin, Ricardo Henao:
Enabling counterfactual survival analysis with balanced representations. CHIL 2021: 133-145 - [c292]Dhanasekar Sundararaman, Vivek Subramanian, Guoyin Wang, Shijing Si, Dinghan Shen, Dong Wang, Lawrence Carin:
Syntactic Knowledge-Infused Transformer and BERT Models. CIKM Workshops 2021 - [c291]Weituo Hao, Mostafa El-Khamy, Jungwon Lee, Jianyi Zhang, Kevin J. Liang, Changyou Chen, Lawrence Carin:
Towards Fair Federated Learning With Zero-Shot Data Augmentation. CVPR Workshops 2021: 3310-3319 - [c290]Vinay Kumar Verma, Kevin J. Liang, Nikhil Mehta, Piyush Rai, Lawrence Carin:
Efficient Feature Transformations for Discriminative and Generative Continual Learning. CVPR 2021: 13865-13875 - [c289]Liqun Chen, Dong Wang, Zhe Gan, Jingjing Liu, Ricardo Henao, Lawrence Carin:
Wasserstein Contrastive Representation Distillation. CVPR 2021: 16296-16305 - [c288]Dhanasekar Sundararaman, Henry Tsai, Kuang-Huei Lee, Iulia Turc, Lawrence Carin:
Learning Task Sampling Policy for Multitask Learning. EMNLP (Findings) 2021: 4410-4415 - [c287]Pengyu Cheng, Weituo Hao, Siyang Yuan, Shijing Si, Lawrence Carin:
FairFil: Contrastive Neural Debiasing Method for Pretrained Text Encoders. ICLR 2021 - [c286]Kevin J. Liang, Weituo Hao, Dinghan Shen, Yufan Zhou, Weizhu Chen, Changyou Chen, Lawrence Carin:
MixKD: Towards Efficient Distillation of Large-scale Language Models. ICLR 2021 - [c285]Siyang Yuan, Pengyu Cheng, Ruiyi Zhang, Weituo Hao, Zhe Gan, Lawrence Carin:
Improving Zero-Shot Voice Style Transfer via Disentangled Representation Learning. ICLR 2021 - [c284]Qian Yang, Jianyi Zhang, Weituo Hao, Gregory P. Spell, Lawrence Carin:
FLOP: Federated Learning on Medical Datasets using Partial Networks. KDD 2021: 3845-3853 - [c283]Shuyang Dai, Zhe Gan, Yu Cheng, Chenyang Tao, Lawrence Carin, Jingjing Liu:
APo-VAE: Text Generation in Hyperbolic Space. NAACL-HLT 2021: 416-431 - [c282]Vivek Subramanian, Matthew Engelhard, Samuel Berchuck, Liqun Chen, Ricardo Henao, Lawrence Carin:
SpanPredict: Extraction of Predictive Document Spans with Neural Attention. NAACL-HLT 2021: 5234-5258 - [c281]Sakshi Varshney, Vinay Kumar Verma, P. K. Srijith, Lawrence Carin, Piyush Rai:
CAM-GAN: Continual Adaptation Modules for Generative Adversarial Networks. NeurIPS 2021: 15175-15187 - [c280]Junya Chen, Zidi Xiu, Benjamin Goldstein, Ricardo Henao, Lawrence Carin, Chenyang Tao:
Supercharging Imbalanced Data Learning With Energy-based Contrastive Representation Transfer. NeurIPS 2021: 21229-21243 - [c279]Wenlin Wang, Hongteng Xu, Guoyin Wang, Wenqi Wang, Lawrence Carin:
Zero-Shot Recognition via Optimal Transport. WACV 2021: 3470-3480 - [i166]Yehua Wei, Lei Zhang, Ruiyi Zhang, Shijing Si, Hao Zhang, Lawrence Carin:
Reinforcement Learning for Flexibility Design Problems. CoRR abs/2101.00355 (2021) - [i165]Jiachang Liu, Dinghan Shen, Yizhe Zhang, Bill Dolan, Lawrence Carin, Weizhu Chen:
What Makes Good In-Context Examples for GPT-3? CoRR abs/2101.06804 (2021) - [i164]Qian Yang, Jianyi Zhang, Weituo Hao, Gregory Spell, Lawrence Carin:
FLOP: Federated Learning on Medical Datasets using Partial Networks. CoRR abs/2102.05218 (2021) - [i163]Vinay Kumar Verma, Kevin J. Liang, Nikhil Mehta, Lawrence Carin:
Meta-Learned Attribute Self-Gating for Continual Generalized Zero-Shot Learning. CoRR abs/2102.11856 (2021) - [i162]Sakshi Varshney, Vinay Kumar Verma, Lawrence Carin, Piyush Rai:
Efficient Continual Adaptation for Generative Adversarial Networks. CoRR abs/2103.04032 (2021) - [i161]Pengyu Cheng, Weituo Hao, Siyang Yuan, Shijing Si, Lawrence Carin:
FairFil: Contrastive Neural Debiasing Method for Pretrained Text Encoders. CoRR abs/2103.06413 (2021) - [i160]Siyang Yuan, Pengyu Cheng, Ruiyi Zhang, Weituo Hao, Zhe Gan, Lawrence Carin:
Improving Zero-shot Voice Style Transfer via Disentangled Representation Learning. CoRR abs/2103.09420 (2021) - [i159]Vinay Kumar Verma, Kevin J. Liang, Nikhil Mehta, Piyush Rai, Lawrence Carin:
Efficient Feature Transformations for Discriminative and Generative Continual Learning. CoRR abs/2103.13558 (2021) - [i158]Meng Xia, Meenal K. Kheterpal, Samantha C. Wong, Christine Park, William Ratliff, Lawrence Carin, Ricardo Henao:
Malignancy Prediction and Lesion Identification from Clinical Dermatological Images. CoRR abs/2104.02652 (2021) - [i157]Weituo Hao, Mostafa El-Khamy, Jungwon Lee, Jianyi Zhang, Kevin J. Liang, Changyou Chen, Lawrence Carin:
Towards Fair Federated Learning with Zero-Shot Data Augmentation. CoRR abs/2104.13417 (2021) - [i156]Qing Guo, Junya Chen, Dong Wang, Yuewei Yang, Xinwei Deng, Lawrence Carin, Fan Li, Chenyang Tao:
Tight Mutual Information Estimation With Contrastive Fenchel-Legendre Optimization. CoRR abs/2107.01131 (2021) - [i155]Junya Chen, Zhe Gan, Xuan Li, Qing Guo, Liqun Chen, Shuyang Gao, Tagyoung Chung, Yi Xu, Belinda Zeng, Wenlian Lu, Fan Li, Lawrence Carin, Chenyang Tao:
Simpler, Faster, Stronger: Breaking The log-K Curse On Contrastive Learners With FlatNCE. CoRR abs/2107.01152 (2021) - [i154]Qitong Gao, Dong Wang, Joshua D. Amason, Siyang Yuan, Chenyang Tao, Ricardo Henao, Majda Hadziahmetovic, Lawrence Carin, Miroslav Pajic:
Imputation-Free Learning from Incomplete Observations. CoRR abs/2107.01983 (2021) - [i153]Serge Assaad, Shuxi Zeng, Henry D. Pfister, Fan Li, Lawrence Carin:
Hölder Bounds for Sensitivity Analysis in Causal Reasoning. CoRR abs/2107.04661 (2021) - [i152]Junya Chen, Danni Lu, Zidi Xiu, Ke Bai, Lawrence Carin, Chenyang Tao:
Variational Inference with Holder Bounds. CoRR abs/2111.02947 (2021) - [i151]Junya Chen, Sijia Wang, Lawrence Carin, Chenyang Tao:
Finite-Time Consensus Learning for Decentralized Optimization with Nonlinear Gossiping. CoRR abs/2111.02949 (2021) - [i150]Rachel Lea Draelos, Lawrence Carin:
Explainable multiple abnormality classification of chest CT volumes with AxialNet and HiResCAM. CoRR abs/2111.12215 (2021) - 2020
- [c278]Wenlin Wang, Hongteng Xu, Zhe Gan, Bai Li, Guoyin Wang, Liqun Chen, Qian Yang, Wenqi Wang, Lawrence Carin:
Graph-Driven Generative Models for Heterogeneous Multi-Task Learning. AAAI 2020: 979-988 - [c277]Miaoyun Zhao, Yulai Cong, Shuyang Dai, Lawrence Carin:
Bridging Maximum Likelihood and Adversarial Learning via α-Divergence. AAAI 2020: 6901-6908 - [c276]Liqun Chen, Ke Bai, Chenyang Tao, Yizhe Zhang, Guoyin Wang, Wenlin Wang, Ricardo Henao, Lawrence Carin:
Sequence Generation with Optimal-Transport-Enhanced Reinforcement Learning. AAAI 2020: 7512-7520 - [c275]Pengyu Cheng, Yitong Li, Xinyuan Zhang, Liqun Chen, David E. Carlson, Lawrence Carin:
Dynamic Embedding on Textual Networks via a Gaussian Process. AAAI 2020: 7562-7569 - [c274]Yuan Li, Chunyuan Li, Yizhe Zhang, Xiujun Li, Guoqing Zheng, Lawrence Carin, Jianfeng Gao:
Complementary Auxiliary Classifiers for Label-Conditional Text Generation. AAAI 2020: 8303-8310 - [c273]Shuyang Dai, Yu Cheng, Yizhe Zhang, Zhe Gan, Jingjing Liu, Lawrence Carin:
Contrastively Smoothed Class Alignment for Unsupervised Domain Adaptation. ACCV (4) 2020: 268-283 - [c272]Ruiyi Zhang, Changyou Chen, Zhe Gan, Wenlin Wang, Dinghan Shen, Guoyin Wang, Zheng Wen, Lawrence Carin:
Improving Adversarial Text Generation by Modeling the Distant Future. ACL 2020: 2516-2531 - [c271]Pengyu Cheng, Martin Renqiang Min, Dinghan Shen, Christopher Malon, Yizhe Zhang, Yitong Li, Lawrence Carin:
Improving Disentangled Text Representation Learning with Information-Theoretic Guidance. ACL 2020: 7530-7541 - [c270]Ruiyi Zhang, Changyou Chen, Zhe Gan, Zheng Wen, Wenlin Wang, Lawrence Carin:
Nested-Wasserstein Self-Imitation Learning for Sequence Generation. AISTATS 2020: 422-433 - [c269]Jianyi Zhang, Ruiyi Zhang, Lawrence Carin, Changyou Chen:
Stochastic Particle-Optimization Sampling and the Non-Asymptotic Convergence Theory. AISTATS 2020: 1877-1887 - [c268]Shuyang Dai, Kihyuk Sohn, Yi-Hsuan Tsai, Lawrence Carin, Manmohan Chandraker:
Adaptation Across Extreme Variations using Unlabeled Bridges. BMVC 2020 - [c267]Yuewei Yang, Kevin J. Liang, Lawrence Carin:
Object Detection as a Positive-Unlabeled Problem. BMVC 2020 - [c266]Siyang Yuan, Ke Bai, Liqun Chen, Yizhe Zhang, Chenyang Tao, Chunyuan Li, Guoyin Wang, Ricardo Henao, Lawrence Carin:
Advancing weakly supervised cross-domain alignment with optimal transport. BMVC 2020 - [c265]Paidamoyo Chapfuwa, Chunyuan Li, Nikhil Mehta, Lawrence Carin, Ricardo Henao:
Survival cluster analysis. CHIL 2020: 60-68 - [c264]Yantao Lu, Yunhan Jia, Jianyu Wang, Bai Li, Weiheng Chai, Lawrence Carin, Senem Velipasalar:
Enhancing Cross-Task Black-Box Transferability of Adversarial Examples With Dispersion Reduction. CVPR 2020: 937-946 - [c263]Weituo Hao, Chunyuan Li, Xiujun Li, Lawrence Carin, Jianfeng Gao:
Towards Learning a Generic Agent for Vision-and-Language Navigation via Pre-Training. CVPR 2020: 13134-13143 - [c262]John McManigle, Raquel Bartz, Lawrence Carin:
Y-Net for Chest X-Ray Preprocessing: Simultaneous Classification of Geometry and Segmentation of Annotations. EMBC 2020: 1266-1269 - [c261]Ruiyi Zhang, Changyou Chen, Xinyuan Zhang, Ke Bai, Lawrence Carin:
Semantic Matching via Optimal Partial Transport. EMNLP (Findings) 2020: 212-222 - [c260]Gregory Spell, Brian Guay, Sunshine Hillygus, Lawrence Carin:
An Embedding Model for Estimating Legislative Preferences from the Frequency and Sentiment of Tweets. EMNLP (1) 2020: 627-641 - [c259]Rui Wang, Shijing Si, Guoyin Wang, Lei Zhang, Lawrence Carin, Ricardo Henao:
Integrating Task Specific Information into Pretrained Language Models for Low Resource Fine Tuning. EMNLP (Findings) 2020: 3181-3186 - [c258]Dhanasekar Sundararaman, Shijing Si, Vivek Subramanian, Guoyin Wang, Devamanyu Hazarika, Lawrence Carin:
Methods for Numeracy-Preserving Word Embeddings. EMNLP (1) 2020: 4742-4753 - [c257]Jianqiao Li, Chunyuan Li, Guoyin Wang, Hao Fu, Yuh-Chen Lin, Liqun Chen, Yizhe Zhang, Chenyang Tao, Ruiyi Zhang, Wenlin Wang, Dinghan Shen, Qian Yang, Lawrence Carin:
Improving Text Generation with Student-Forcing Optimal Transport. EMNLP (1) 2020: 9144-9156 - [c256]Nathan Inkawhich, Kevin J. Liang, Lawrence Carin, Yiran Chen:
Transferable Perturbations of Deep Feature Distributions. ICLR 2020 - [c255]Sam Lobel, Chunyuan Li, Jianfeng Gao, Lawrence Carin:
RaCT: Toward Amortized Ranking-Critical Training For Collaborative Filtering. ICLR 2020 - [c254]Liqun Chen, Zhe Gan, Yu Cheng, Linjie Li, Lawrence Carin, Jingjing Liu:
Graph Optimal Transport for Cross-Domain Alignment. ICML 2020: 1542-1553 - [c253]Pengyu Cheng, Weituo Hao, Shuyang Dai, Jiachang Liu, Zhe Gan, Lawrence Carin:
CLUB: A Contrastive Log-ratio Upper Bound of Mutual Information. ICML 2020: 1779-1788 - [c252]Hongteng Xu, Dixin Luo, Ricardo Henao, Svati Shah, Lawrence Carin:
Learning Autoencoders with Relational Regularization. ICML 2020: 10576-10586 - [c251]Miaoyun Zhao, Yulai Cong, Lawrence Carin:
On Leveraging Pretrained GANs for Generation with Limited Data. ICML 2020: 11340-11351 - [c250]Shijing Si, Chris J. Oates, Andrew B. Duncan, Lawrence Carin, François-Xavier Briol:
Scalable Control Variates for Monte Carlo Methods Via Stochastic Optimization. MCQMC 2020: 205-221 - [c249]Shijing Si, Rui Wang, Jedrek Wosik, Hao Zhang, David Dov, Guoyin Wang, Lawrence Carin:
Students Need More Attention: BERT-based Attention Model for Small Data with Application to Automatic Patient Message Triage. MLHC 2020: 436-456 - [c248]Hao Zhang, Yuan Li, Zhijie Deng, Xiaodan Liang, Lawrence Carin, Eric P. Xing:
AutoSync: Learning to Synchronize for Data-Parallel Distributed Deep Learning. NeurIPS 2020 - [c247]Yulai Cong, Miaoyun Zhao, Jianqiao Li, Sijia Wang, Lawrence Carin:
GAN Memory with No Forgetting. NeurIPS 2020 - [c246]Nathan Inkawhich, Kevin J. Liang, Binghui Wang, Matthew Inkawhich, Lawrence Carin, Yiran Chen:
Perturbing Across the Feature Hierarchy to Improve Standard and Strict Blackbox Attack Transferability. NeurIPS 2020 - [c245]Danni Lu, Chenyang Tao, Junya Chen, Fan Li, Feng Guo, Lawrence Carin:
Reconsidering Generative Objectives For Counterfactual Reasoning. NeurIPS 2020 - [c244]Pravendra Singh, Vinay Kumar Verma, Pratik Mazumder, Lawrence Carin, Piyush Rai:
Calibrating CNNs for Lifelong Learning. NeurIPS 2020 - [i149]Ruiyi Zhang, Changyou Chen, Zhe Gan, Zheng Wen, Wenlin Wang, Lawrence Carin:
Nested-Wasserstein Self-Imitation Learning for Sequence Generation. CoRR abs/2001.06944 (2020) - [i148]Zhouyuan Huo, Qian Yang, Bin Gu, Lawrence Carin, Heng Huang:
Faster On-Device Training Using New Federated Momentum Algorithm. CoRR abs/2002.02090 (2020) - [i147]Hongteng Xu, Dixin Luo, Ricardo Henao, Svati Shah, Lawrence Carin:
Learning Autoencoders with Relational Regularization. CoRR abs/2002.02913 (2020) - [i146]Yuewei Yang, Kevin J. Liang, Lawrence Carin:
Object Detection as a Positive-Unlabeled Problem. CoRR abs/2002.04672 (2020) - [i145]Rachel Lea Draelos, David Dov, Maciej A. Mazurowski, Joseph Y. Lo, Ricardo Henao, Geoffrey D. Rubin, Lawrence Carin:
Machine-Learning-Based Multiple Abnormality Prediction with Large-Scale Chest Computed Tomography Volumes. CoRR abs/2002.04752 (2020) - [i144]Weituo Hao, Chunyuan Li, Xiujun Li, Lawrence Carin, Jianfeng Gao:
Towards Learning a Generic Agent for Vision-and-Language Navigation via Pre-training. CoRR abs/2002.10638 (2020) - [i143]Miaoyun Zhao, Yulai Cong, Lawrence Carin:
On Leveraging Pretrained GANs for Limited-Data Generation. CoRR abs/2002.11810 (2020) - [i142]Paidamoyo Chapfuwa, Chunyuan Li, Nikhil Mehta, Lawrence Carin, Ricardo Henao:
Survival Cluster Analysis. CoRR abs/2003.00355 (2020) - [i141]Bai Li, Shiqi Wang, Yunhan Jia, Yantao Lu, Zhenyu Zhong, Lawrence Carin, Suman Jana:
Towards Practical Lottery Ticket Hypothesis for Adversarial Training. CoRR abs/2003.05733 (2020) - [i140]Nikhil Mehta, Kevin J. Liang, Lawrence Carin:
Bayesian Nonparametric Weight Factorization for Continual Learning. CoRR abs/2004.10098 (2020) - [i139]Nathan Inkawhich, Kevin J. Liang, Lawrence Carin, Yiran Chen:
Transferable Perturbations of Deep Feature Distributions. CoRR abs/2004.12519 (2020) - [i138]Nathan Inkawhich, Kevin J. Liang, Binghui Wang, Matthew Inkawhich, Lawrence Carin, Yiran Chen:
Perturbing Across the Feature Hierarchy to Improve Standard and Strict Blackbox Attack Transferability. CoRR abs/2004.14861 (2020) - [i137]Shuyang Dai, Zhe Gan, Yu Cheng, Chenyang Tao, Lawrence Carin, Jingjing Liu:
APo-VAE: Text Generation in Hyperbolic Space. CoRR abs/2005.00054 (2020) - [i136]Ruiyi Zhang, Changyou Chen, Zhe Gan, Wenlin Wang, Dinghan Shen, Guoyin Wang, Zheng Wen, Lawrence Carin:
Improving Adversarial Text Generation by Modeling the Distant Future. CoRR abs/2005.01279 (2020) - [i135]Ruiyi Zhang, Tong Yu, Yilin Shen, Hongxia Jin, Changyou Chen, Lawrence Carin:
Reward Constrained Interactive Recommendation with Natural Language Feedback. CoRR abs/2005.01618 (2020) - [i134]John McManigle, Raquel Bartz, Lawrence Carin:
Y-Net for Chest X-Ray Preprocessing: Simultaneous Classification of Geometry and Segmentation of Annotations. CoRR abs/2005.03824 (2020) - [i133]Pengyu Cheng, Martin Renqiang Min, Dinghan Shen, Christopher Malon, Yizhe Zhang, Yitong Li, Lawrence Carin:
Improving Disentangled Text Representation Learning with Information-Theoretic Guidance. CoRR abs/2006.00693 (2020) - [i132]Bai Li, Shiqi Wang, Suman Jana, Lawrence Carin:
Towards Understanding Fast Adversarial Training. CoRR abs/2006.03089 (2020) - [i131]Dixin Luo, Hongteng Xu, Lawrence Carin:
Hierarchical Optimal Transport for Robust Multi-View Learning. CoRR abs/2006.03160 (2020) - [i130]Shijing Si, Chris J. Oates, Andrew B. Duncan, Lawrence Carin, François-Xavier Briol:
Scalable Control Variates for Monte Carlo Methods via Stochastic Optimization. CoRR abs/2006.07487 (2020) - [i129]Yulai Cong, Miaoyun Zhao, Jianqiao Li, Sijia Wang, Lawrence Carin:
GAN Memory with No Forgetting. CoRR abs/2006.07543 (2020) - [i128]Paidamoyo Chapfuwa, Serge Assaad, Shuxi Zeng, Michael J. Pencina, Lawrence Carin, Ricardo Henao:
Survival Analysis meets Counterfactual Inference. CoRR abs/2006.07756 (2020) - [i127]Yulai Cong, Miaoyun Zhao, Jianqiao Li, Junya Chen, Lawrence Carin:
GO Hessian for Expectation-Based Objectives. CoRR abs/2006.08873 (2020) - [i126]Shijing Si, Rui Wang, Jedrek Wosik, Hao Zhang, David Dov, Guoyin Wang, Ricardo Henao, Lawrence Carin:
Students Need More Attention: BERT-based AttentionModel for Small Data with Application to AutomaticPatient Message Triage. CoRR abs/2006.11991 (2020) - [i125]Pengyu Cheng, Weituo Hao, Shuyang Dai, Jiachang Liu, Zhe Gan, Lawrence Carin:
CLUB: A Contrastive Log-ratio Upper Bound of Mutual Information. CoRR abs/2006.12013 (2020) - [i124]Liqun Chen, Zhe Gan, Yu Cheng, Linjie Li, Lawrence Carin, Jingjing Liu:
Graph Optimal Transport for Cross-Domain Alignment. CoRR abs/2006.14744 (2020) - [i123]Miaoyun Zhao, Yulai Cong, Shuyang Dai, Lawrence Carin:
Bridging Maximum Likelihood and Adversarial Learning via α-Divergence. CoRR abs/2007.06178 (2020) - [i122]Weituo Hao, Nikhil Mehta, Kevin J. Liang, Pengyu Cheng, Mostafa El-Khamy, Lawrence Carin:
WAFFLe: Weight Anonymized Factorization for Federated Learning. CoRR abs/2008.05687 (2020) - [i121]Siyang Yuan, Ke Bai, Liqun Chen, Yizhe Zhang, Chenyang Tao, Chunyuan Li, Guoyin Wang, Ricardo Henao, Lawrence Carin:
Weakly supervised cross-domain alignment with optimal transport. CoRR abs/2008.06597 (2020) - [i120]John B. Sigman, Gregory P. Spell, Kevin J. Liang, Lawrence Carin:
Background Adaptive Faster R-CNN for Semi-Supervised Convolutional Object Detection of Threats in X-Ray Images. CoRR abs/2010.01202 (2020) - [i119]Guoyin Wang, Chunyuan Li, Jianqiao Li, Hao Fu, Yuh-Chen Lin, Liqun Chen, Yizhe Zhang, Chenyang Tao, Ruiyi Zhang, Wenlin Wang, Dinghan Shen, Qian Yang, Lawrence Carin:
Improving Text Generation with Student-Forcing Optimal Transport. CoRR abs/2010.05994 (2020) - [i118]Shounak Datta, Eduardo B. Mariottoni, David Dov, Alessandro A. Jammal, Lawrence Carin, Felipe A. Medeiros:
RetiNerveNet: Using Recursive Deep Learning to Estimate Pointwise 24-2 Visual Field Data based on Retinal Structure. CoRR abs/2010.07488 (2020) - [i117]Shuxi Zeng, Serge Assaad, Chenyang Tao, Shounak Datta, Lawrence Carin, Fan Li:
Double Robust Representation Learning for Counterfactual Prediction. CoRR abs/2010.07866 (2020) - [i116]Serge Assaad, Shuxi Zeng, Chenyang Tao, Shounak Datta, Nikhil Mehta, Ricardo Henao, Fan Li, Lawrence Carin:
Counterfactual Representation Learning with Balancing Weights. CoRR abs/2010.12618 (2020) - [i115]Kevin J. Liang, Weituo Hao, Dinghan Shen, Yufan Zhou, Weizhu Chen, Changyou Chen, Lawrence Carin:
MixKD: Towards Efficient Distillation of Large-scale Language Models. CoRR abs/2011.00593 (2020) - [i114]Pengyu Cheng, Weituo Hao, Lawrence Carin:
Estimating Total Correlation with Mutual Information Bounds. CoRR abs/2011.04794 (2020) - [i113]Rachel Lea Draelos, Lawrence Carin:
HiResCAM: Explainable Multi-Organ Multi-Abnormality Prediction in 3D Medical Images. CoRR abs/2011.08891 (2020) - [i112]Junya Chen, Zidi Xiu, Benjamin Alan Goldstein, Ricardo Henao, Lawrence Carin, Chenyang Tao:
Supercharging Imbalanced Data Learning With Causal Representation Transfer. CoRR abs/2011.12454 (2020) - [i111]Dong Wang, Yuewei Yang, Chenyang Tao, Fanjie Kong, Ricardo Henao, Lawrence Carin:
Proactive Pseudo-Intervention: Causally Informed Contrastive Learning For Interpretable Vision Models. CoRR abs/2012.03369 (2020) - [i110]Hongteng Xu, Dixin Luo, Lawrence Carin, Hongyuan Zha:
Learning Graphons via Structured Gromov-Wasserstein Barycenters. CoRR abs/2012.05644 (2020) - [i109]Liqun Chen, Zhe Gan, Dong Wang, Jingjing Liu, Ricardo Henao, Lawrence Carin:
Wasserstein Contrastive Representation Distillation. CoRR abs/2012.08674 (2020)
2010 – 2019
- 2019
- [j114]Changyou Chen, Wenlin Wang, Yizhe Zhang, Qinliang Su, Lawrence Carin:
A convergence analysis for a class of practical variance-reduction stochastic gradient MCMC. Sci. China Inf. Sci. 62(1): 12101:1-12101:13 (2019) - [c243]Chunyuan Li, Changyou Chen, Yunchen Pu, Ricardo Henao, Lawrence Carin:
Communication-Efficient Stochastic Gradient MCMC for Neural Networks. AAAI 2019: 4173-4180 - [c242]Dinghan Shen, Pengyu Cheng, Dhanasekar Sundararaman, Xinyuan Zhang, Qian Yang, Meng Tang, Asli Celikyilmaz, Lawrence Carin:
Learning Compressed Sentence Representations for On-Device Text Processing. ACL (1) 2019: 107-116 - [c241]Xinyuan Zhang, Yi Yang, Siyang Yuan, Dinghan Shen, Lawrence Carin:
Syntax-Infused Variational Autoencoder for Text Generation. ACL (1) 2019: 2069-2078 - [c240]Dinghan Shen, Asli Celikyilmaz, Yizhe Zhang, Liqun Chen, Xin Wang, Jianfeng Gao, Lawrence Carin:
Towards Generating Long and Coherent Text with Multi-Level Latent Variable Models. ACL (1) 2019: 2079-2089 - [c239]Liqun Chen, Guoyin Wang, Chenyang Tao, Dinghan Shen, Pengyu Cheng, Xinyuan Zhang, Wenlin Wang, Yizhe Zhang, Lawrence Carin:
Improving Textual Network Embedding with Global Attention via Optimal Transport. ACL (1) 2019: 5193-5202 - [c238]Ruiyi Zhang, Zheng Wen, Changyou Chen, Chen Fang, Tong Yu, Lawrence Carin:
Scalable Thompson Sampling via Optimal Transport. AISTATS 2019: 87-96 - [c237]Bai Li, Changyou Chen, Hao Liu, Lawrence Carin:
On Connecting Stochastic Gradient MCMC and Differential Privacy. AISTATS 2019: 557-566 - [c236]Chunyuan Li, Ke Bai, Jianqiao Li, Guoyin Wang, Changyou Chen, Lawrence Carin:
Adversarial Learning of a Sampler Based on an Unnormalized Distribution. AISTATS 2019: 3302-3311 - [c235]Yitong Li, Zhe Gan, Yelong Shen, Jingjing Liu, Yu Cheng, Yuexin Wu, Lawrence Carin, David E. Carlson, Jianfeng Gao:
StoryGAN: A Sequential Conditional GAN for Story Visualization. CVPR 2019: 6329-6338 - [c234]Qian Yang, Zhouyuan Huo, Dinghan Shen, Yong Cheng, Wenlin Wang, Guoyin Wang, Lawrence Carin:
An End-to-End Generative Architecture for Paraphrase Generation. EMNLP/IJCNLP (1) 2019: 3130-3140 - [c233]Liqun Chen, Yizhe Zhang, Ruiyi Zhang, Chenyang Tao, Zhe Gan, Haichao Zhang, Bai Li, Dinghan Shen, Changyou Chen, Lawrence Carin:
Improving Sequence-to-Sequence Learning via Optimal Transport. ICLR (Poster) 2019 - [c232]Yulai Cong, Miaoyun Zhao, Ke Bai, Lawrence Carin:
GO Gradient for Expectation-Based Objectives. ICLR (Poster) 2019 - [c231]Nikhil Mehta, Lawrence Carin, Piyush Rai:
Stochastic Blockmodels meet Graph Neural Networks. ICML 2019: 4466-4474 - [c230]Zhao Song, Ronald Parr, Lawrence Carin:
Revisiting the Softmax Bellman Operator: New Benefits and New Perspective. ICML 2019: 5916-5925 - [c229]Chenyang Tao, Shuyang Dai, Liqun Chen, Ke Bai, Junya Chen, Chang Liu, Ruiyi Zhang, Georgiy V. Bobashev, Lawrence Carin:
Variational Annealing of GANs: A Langevin Perspective. ICML 2019: 6176-6185 - [c228]Hongteng Xu, Dixin Luo, Hongyuan Zha, Lawrence Carin:
Gromov-Wasserstein Learning for Graph Matching and Node Embedding. ICML 2019: 6932-6941 - [c227]David Dov, Shahar Z. Kovalsky, Jonathan Cohen, Danielle Elliott Range, Ricardo Henao, Lawrence Carin:
Thyroid Cancer Malignancy Prediction From Whole Slide Cytopathology Images. MLHC 2019: 553-570 - [c226]Wenlin Wang, Zhe Gan, Hongteng Xu, Ruiyi Zhang, Guoyin Wang, Dinghan Shen, Changyou Chen, Lawrence Carin:
Topic-Guided Variational Auto-Encoder for Text Generation. NAACL-HLT (1) 2019: 166-177 - [c225]Hao Fu, Chunyuan Li, Xiaodong Liu, Jianfeng Gao, Asli Celikyilmaz, Lawrence Carin:
Cyclical Annealing Schedule: A Simple Approach to Mitigating KL Vanishing. NAACL-HLT (1) 2019: 240-250 - [c224]Wenlin Wang, Chenyang Tao, Zhe Gan, Guoyin Wang, Liqun Chen, Xinyuan Zhang, Ruiyi Zhang, Qian Yang, Ricardo Henao, Lawrence Carin:
Improving Textual Network Learning with Variational Homophilic Embeddings. NeurIPS 2019: 2074-2085 - [c223]Hongteng Xu, Dixin Luo, Lawrence Carin:
Scalable Gromov-Wasserstein Learning for Graph Partitioning and Matching. NeurIPS 2019: 3046-3056 - [c222]Kevin J. Liang, Guoyin Wang, Yitong Li, Ricardo Henao, Lawrence Carin:
Kernel-Based Approaches for Sequence Modeling: Connections to Neural Methods. NeurIPS 2019: 3387-3398 - [c221]Qian Yang, Zhouyuan Huo, Wenlin Wang, Heng Huang, Lawrence Carin:
Ouroboros: On Accelerating Training of Transformer-Based Language Models. NeurIPS 2019: 5520-5530 - [c220]Bai Li, Changyou Chen, Wenlin Wang, Lawrence Carin:
Certified Adversarial Robustness with Additive Noise. NeurIPS 2019: 9459-9469 - [c219]Chenyang Tao, Liqun Chen, Shuyang Dai, Junya Chen, Ke Bai, Dong Wang, Jianfeng Feng, Wenlian Lu, Georgiy V. Bobashev, Lawrence Carin:
On Fenchel Mini-Max Learning. NeurIPS 2019: 10427-10439 - [i108]Chunyuan Li, Ke Bai, Jianqiao Li, Guoyin Wang, Changyou Chen, Lawrence Carin:
Adversarial Learning of a Sampler Based on an Unnormalized Distribution. CoRR abs/1901.00612 (2019) - [i107]Hongteng Xu, Dixin Luo, Hongyuan Zha, Lawrence Carin:
Gromov-Wasserstein Learning for Graph Matching and Node Embedding. CoRR abs/1901.06003 (2019) - [i106]Yulai Cong, Miaoyun Zhao, Ke Bai, Lawrence Carin:
GO Gradient for Expectation-Based Objectives. CoRR abs/1901.06020 (2019) - [i105]Liqun Chen, Yizhe Zhang, Ruiyi Zhang, Chenyang Tao, Zhe Gan, Haichao Zhang, Bai Li, Dinghan Shen, Changyou Chen, Lawrence Carin:
Improving Sequence-to-Sequence Learning via Optimal Transport. CoRR abs/1901.06283 (2019) - [i104]Dinghan Shen, Asli Celikyilmaz, Yizhe Zhang, Liqun Chen, Xin Wang, Jianfeng Gao, Lawrence Carin:
Towards Generating Long and Coherent Text with Multi-Level Latent Variable Models. CoRR abs/1902.00154 (2019) - [i103]Ruiyi Zhang, Zheng Wen, Changyou Chen, Lawrence Carin:
Scalable Thompson Sampling via Optimal Transport. CoRR abs/1902.07239 (2019) - [i102]Wenlin Wang, Zhe Gan, Hongteng Xu, Ruiyi Zhang, Guoyin Wang, Dinghan Shen, Changyou Chen, Lawrence Carin:
Topic-Guided Variational Autoencoders for Text Generation. CoRR abs/1903.07137 (2019) - [i101]Hao Fu, Chunyuan Li, Xiaodong Liu, Jianfeng Gao, Asli Celikyilmaz, Lawrence Carin:
Cyclical Annealing Schedule: A Simple Approach to Mitigating KL Vanishing. CoRR abs/1903.10145 (2019) - [i100]David Dov, Shahar Ziv Kovalsky, Jonathan Cohen, Danielle Range, Ricardo Henao, Lawrence Carin:
Thyroid Cancer Malignancy Prediction From Whole Slide Cytopathology Images. CoRR abs/1904.00839 (2019) - [i99]David Dov, Shahar Ziv Kovalsky, Jonathan Cohen, Danielle Elliott Range, Ricardo Henao, Lawrence Carin:
A Deep-Learning Algorithm for Thyroid Malignancy Prediction From Whole Slide Cytopathology Images. CoRR abs/1904.12739 (2019) - [i98]Nikhil Mehta, Lawrence Carin, Piyush Rai:
Stochastic Blockmodels meet Graph Neural Networks. CoRR abs/1905.05738 (2019) - [i97]Bai Li, Changyou Chen, Wenlin Wang, Lawrence Carin:
On Norm-Agnostic Robustness of Adversarial Training. CoRR abs/1905.06455 (2019) - [i96]Hongteng Xu, Dixin Luo, Lawrence Carin:
Scalable Gromov-Wasserstein Learning for Graph Partitioning and Matching. CoRR abs/1905.07645 (2019) - [i95]Paidamoyo Chapfuwa, Chenyang Tao, Lawrence Carin, Ricardo Henao:
Survival Function Matching for Calibrated Time-to-Event Predictions. CoRR abs/1905.08838 (2019) - [i94]Liqun Chen, Guoyin Wang, Chenyang Tao, Dinghan Shen, Pengyu Cheng, Xinyuan Zhang, Wenlin Wang, Yizhe Zhang, Lawrence Carin:
Improving Textual Network Embedding with Global Attention via Optimal Transport. CoRR abs/1906.01840 (2019) - [i93]Xinyuan Zhang, Yi Yang, Siyang Yuan, Dinghan Shen, Lawrence Carin:
Syntax-Infused Variational Autoencoder for Text Generation. CoRR abs/1906.02181 (2019) - [i92]Shuyang Dai, Kihyuk Sohn, Yi-Hsuan Tsai, Lawrence Carin, Manmohan Chandraker:
Adaptation Across Extreme Variations using Unlabeled Domain Bridges. CoRR abs/1906.02238 (2019) - [i91]Sam Lobel, Chunyuan Li, Jianfeng Gao, Lawrence Carin:
Towards Amortized Ranking-Critical Training for Collaborative Filtering. CoRR abs/1906.04281 (2019) - [i90]Dixin Luo, Hongteng Xu, Lawrence Carin:
Interpretable ICD Code Embeddings with Self- and Mutual-Attention Mechanisms. CoRR abs/1906.05492 (2019) - [i89]Dinghan Shen, Pengyu Cheng, Dhanasekar Sundararaman, Xinyuan Zhang, Qian Yang, Meng Tang, Asli Celikyilmaz, Lawrence Carin:
Learning Compressed Sentence Representations for On-Device Text Processing. CoRR abs/1906.08340 (2019) - [i88]Dixin Luo, Hongteng Xu, Lawrence Carin:
Adversarial Self-Paced Learning for Mixture Models of Hawkes Processes. CoRR abs/1906.08397 (2019) - [i87]Dong Wang, Yitong Li, Wei Cao, Liqun Chen, Qi Wei, Lawrence Carin:
LMVP: Video Predictor with Leaked Motion Information. CoRR abs/1906.10101 (2019) - [i86]Shuyang Dai, Yu Cheng, Yizhe Zhang, Zhe Gan, Jingjing Liu, Lawrence Carin:
Contrastively Smoothed Class Alignment for Unsupervised Domain Adaptation. CoRR abs/1909.05288 (2019) - [i85]Qian Yang, Zhouyuan Huo, Wenlin Wang, Heng Huang, Lawrence Carin:
Ouroboros: On Accelerating Training of Transformer-Based Language Models. CoRR abs/1909.06695 (2019) - [i84]Wenlin Wang, Chenyang Tao, Zhe Gan, Guoyin Wang, Liqun Chen, Xinyuan Zhang, Ruiyi Zhang, Qian Yang, Ricardo Henao, Lawrence Carin:
Improving Textual Network Learning with Variational Homophilic Embeddings. CoRR abs/1909.13456 (2019) - [i83]Dixin Luo, Hongteng Xu, Lawrence Carin:
Fused Gromov-Wasserstein Alignment for Hawkes Processes. CoRR abs/1910.02096 (2019) - [i82]Pengyu Cheng, Chang Liu, Chunyuan Li, Dinghan Shen, Ricardo Henao, Lawrence Carin:
Straight-Through Estimator as Projected Wasserstein Gradient Flow. CoRR abs/1910.02176 (2019) - [i81]Pengyu Cheng, Yitong Li, Xinyuan Zhang, Liqun Cheng, David E. Carlson, Lawrence Carin:
Gaussian-Process-Based Dynamic Embedding for Textual Networks. CoRR abs/1910.02187 (2019) - [i80]Kevin J. Liang, Guoyin Wang, Yitong Li, Ricardo Henao, Lawrence Carin:
Kernel-Based Approaches for Sequence Modeling: Connections to Neural Methods. CoRR abs/1910.04233 (2019) - [i79]Wenlin Wang, Hongteng Xu, Guoyin Wang, Wenqi Wang, Lawrence Carin:
An Optimal Transport Framework for Zero-Shot Learning. CoRR abs/1910.09057 (2019) - [i78]Wenlin Wang, Hongteng Xu, Ruiyi Zhang, Wenqi Wang, Lawrence Carin:
Collaborative Filtering with A Synthetic Feedback Loop. CoRR abs/1910.12735 (2019) - [i77]Dhanasekar Sundararaman, Vivek Subramanian, Guoyin Wang, Shijing Si, Dinghan Shen, Dong Wang, Lawrence Carin:
Syntax-Infused Transformer and BERT models for Machine Translation and Natural Language Understanding. CoRR abs/1911.06156 (2019) - [i76]Wenlin Wang, Hongteng Xu, Zhe Gan, Bai Li, Guoyin Wang, Liqun Chen, Qian Yang, Wenqi Wang, Lawrence Carin:
Graph-Driven Generative Models for Heterogeneous Multi-Task Learning. CoRR abs/1911.08709 (2019) - [i75]Yantao Lu, Yunhan Jia, Jianyu Wang, Bai Li, Weiheng Chai, Lawrence Carin, Senem Velipasalar:
Enhancing Cross-task Black-Box Transferability of Adversarial Examples with Dispersion Reduction. CoRR abs/1911.11616 (2019) - [i74]Kevin J. Liang, John B. Sigman, Gregory P. Spell, Dan Strellis, William Chang, Felix Liu, Tejas Mehta, Lawrence Carin:
Toward Automatic Threat Recognition for Airport X-ray Baggage Screening with Deep Convolutional Object Detection. CoRR abs/1912.06329 (2019) - 2018
- [c218]Wenlin Wang, Yunchen Pu, Vinay Kumar Verma, Kai Fan, Yizhe Zhang, Changyou Chen, Piyush Rai, Lawrence Carin:
Zero-Shot Learning via Class-Conditioned Deep Generative Models. AAAI 2018: 4211-4218 - [c217]Dinghan Shen, Yizhe Zhang, Ricardo Henao, Qinliang Su, Lawrence Carin:
Deconvolutional Latent-Variable Model for Text Sequence Matching. AAAI 2018: 5438-5445 - [c216]Yitong Li, Martin Renqiang Min, Dinghan Shen, David E. Carlson, Lawrence Carin:
Video Generation From Text. AAAI 2018: 7065-7072 - [c215]Yunchen Pu, Martin Renqiang Min, Zhe Gan, Lawrence Carin:
Adaptive Feature Abstraction for Translating Video to Text. AAAI 2018: 7284-7291 - [c214]Dinghan Shen, Guoyin Wang, Wenlin Wang, Martin Renqiang Min, Qinliang Su, Yizhe Zhang, Chunyuan Li, Ricardo Henao, Lawrence Carin:
Baseline Needs More Love: On Simple Word-Embedding-Based Models and Associated Pooling Mechanisms. ACL (1) 2018: 440-450 - [c213]Dinghan Shen, Qinliang Su, Paidamoyo Chapfuwa, Wenlin Wang, Guoyin Wang, Ricardo Henao, Lawrence Carin:
NASH: Toward End-to-End Neural Architecture for Generative Semantic Hashing. ACL (1) 2018: 2041-2050 - [c212]Guoyin Wang, Chunyuan Li, Wenlin Wang, Yizhe Zhang, Dinghan Shen, Xinyuan Zhang, Ricardo Henao, Lawrence Carin:
Joint Embedding of Words and Labels for Text Classification. ACL (1) 2018: 2321-2331 - [c211]Wenlin Wang, Zhe Gan, Wenqi Wang, Dinghan Shen, Jiaji Huang, Wei Ping, Sanjeev Satheesh, Lawrence Carin:
Topic Compositional Neural Language Model. AISTATS 2018: 356-365 - [c210]Hongteng Xu, Dixin Luo, Xu Chen, Lawrence Carin:
Benefits from Superposed Hawkes Processes. AISTATS 2018: 623-631 - [c209]Liqun Chen, Shuyang Dai, Yunchen Pu, Erjin Zhou, Chunyuan Li, Qinliang Su, Changyou Chen, Lawrence Carin:
Symmetric Variational Autoencoder and Connections to Adversarial Learning. AISTATS 2018: 661-669 - [c208]Ruiyi Zhang, Chunyuan Li, Changyou Chen, Lawrence Carin:
Learning Structural Weight Uncertainty for Sequential Decision-Making. AISTATS 2018: 1137-1146 - [c207]Shelley A. Rusincovitch, Lisa Wruck, Ricardo Henao, Larisa Rodgers, Allison Dunning, Peter Merrill, Hillary Mulder, Robert Overton, Matthew Phelan, Erich Huang, Lawrence Carin, Michael J. Pencina:
The Duke Health Data Science Internship Program: Integrating the Educational Mission into Real-World Research. AMIA 2018 - [c206]Xinyuan Zhang, Xin Yuan, Lawrence Carin:
Nonlocal Low-Rank Tensor Factor Analysis for Image Restoration. CVPR 2018: 8232-8241 - [c205]Dinghan Shen, Xinyuan Zhang, Ricardo Henao, Lawrence Carin:
Improved Semantic-Aware Network Embedding with Fine-Grained Word Alignment. EMNLP 2018: 1829-1838 - [c204]Dinghan Shen, Martin Renqiang Min, Yitong Li, Lawrence Carin:
Learning Context-Aware Convolutional Filters for Text Processing. EMNLP 2018: 1839-1848 - [c203]Paidamoyo Chapfuwa, Chenyang Tao, Chunyuan Li, Courtney Page, Benjamin Alan Goldstein, Lawrence Carin, Ricardo Henao:
Adversarial Time-to-Event Modeling. ICML 2018: 734-743 - [c202]Changyou Chen, Chunyuan Li, Liquan Chen, Wenlin Wang, Yunchen Pu, Lawrence Carin:
Continuous-Time Flows for Efficient Inference and Density Estimation. ICML 2018: 823-832 - [c201]Liqun Chen, Chenyang Tao, Ruiyi Zhang, Ricardo Henao, Lawrence Carin:
Variational Inference and Model Selection with Generalized Evidence Bounds. ICML 2018: 892-901 - [c200]Yunchen Pu, Shuyang Dai, Zhe Gan, Weiyao Wang, Guoyin Wang, Yizhe Zhang, Ricardo Henao, Lawrence Carin:
JointGAN: Multi-Domain Joint Distribution Learning with Generative Adversarial Nets. ICML 2018: 4148-4157 - [c199]Chenyang Tao, Liqun Chen, Ricardo Henao, Jianfeng Feng, Lawrence Carin:
Chi-square Generative Adversarial Network. ICML 2018: 4894-4903 - [c198]Hongteng Xu, Lawrence Carin, Hongyuan Zha:
Learning Registered Point Processes from Idiosyncratic Observations. ICML 2018: 5439-5448 - [c197]Ruiyi Zhang, Changyou Chen, Chunyuan Li, Lawrence Carin:
Policy Optimization as Wasserstein Gradient Flows. ICML 2018: 5741-5750 - [c196]Hongteng Xu, Dixin Luo, Lawrence Carin:
Online Continuous-Time Tensor Factorization Based on Pairwise Interactive Point Processes. IJCAI 2018: 2905-2911 - [c195]Qi Wei, Yinhao Ren, Rui Hou, Bibo Shi, Joseph Y. Lo, Lawrence Carin:
Anomaly detection for medical images based on a one-class classification. Computer-Aided Diagnosis 2018: 105751M - [c194]Xinyuan Zhang, Ricardo Henao, Zhe Gan, Yitong Li, Lawrence Carin:
Multi-Label Learning from Medical Plain Text with Convolutional Residual Models. MLHC 2018: 280-294 - [c193]Matthew Engelhard, Hongteng Xu, Lawrence Carin, Jason A. Oliver, Matthew Hallyburton, F. Joseph McClernon:
Predicting Smoking Events with a Time-Varying Semi-Parametric Hawkes Process Model. MLHC 2018: 312-331 - [c192]Hongteng Xu, Wenlin Wang, Wei Liu, Lawrence Carin:
Distilled Wasserstein Learning for Word Embedding and Topic Modeling. NeurIPS 2018: 1723-1732 - [c191]Liqun Chen, Shuyang Dai, Chenyang Tao, Haichao Zhang, Zhe Gan, Dinghan Shen, Yizhe Zhang, Guoyin Wang, Ruiyi Zhang, Lawrence Carin:
Adversarial Text Generation via Feature-Mover's Distance. NeurIPS 2018: 4671-4682 - [c190]Xinyuan Zhang, Yitong Li, Dinghan Shen, Lawrence Carin:
Diffusion Maps for Textual Network Embedding. NeurIPS 2018: 7598-7608 - [i73]Ruiyi Zhang, Chunyuan Li, Changyou Chen, Lawrence Carin:
Learning Structural Weight Uncertainty for Sequential Decision-Making. CoRR abs/1801.00085 (2018) - [i72]Xinyuan Zhang, Ricardo Henao, Zhe Gan, Yitong Li, Lawrence Carin:
Multi-Label Learning from Medical Plain Text with Convolutional Residual Models. CoRR abs/1801.05062 (2018) - [i71]Xinyuan Zhang, Xin Yuan, Lawrence Carin:
Nonlocal Low-Rank Tensor Factor Analysis for Image Restoration. CoRR abs/1803.06795 (2018) - [i70]Paidamoyo Chapfuwa, Chenyang Tao, Chunyuan Li, Courtney Page, Benjamin Alan Goldstein, Lawrence Carin, Ricardo Henao:
Adversarial Time-to-Event Modeling. CoRR abs/1804.03184 (2018) - [i69]Guoyin Wang, Chunyuan Li, Wenlin Wang, Yizhe Zhang, Dinghan Shen, Xinyuan Zhang, Ricardo Henao, Lawrence Carin:
Joint Embedding of Words and Labels for Text Classification. CoRR abs/1805.04174 (2018) - [i68]Dinghan Shen, Qinliang Su, Paidamoyo Chapfuwa, Wenlin Wang, Guoyin Wang, Lawrence Carin, Ricardo Henao:
NASH: Toward End-to-End Neural Architecture for Generative Semantic Hashing. CoRR abs/1805.05361 (2018) - [i67]Dinghan Shen, Guoyin Wang, Wenlin Wang, Martin Renqiang Min, Qinliang Su, Yizhe Zhang, Chunyuan Li, Ricardo Henao, Lawrence Carin:
Baseline Needs More Love: On Simple Word-Embedding-Based Models and Associated Pooling Mechanisms. CoRR abs/1805.09843 (2018) - [i66]Xinyuan Zhang, Yitong Li, Dinghan Shen, Lawrence Carin:
Diffusion Maps for Textual Network Embedding. CoRR abs/1805.09906 (2018) - [i65]Yunchen Pu, Shuyang Dai, Zhe Gan, Weiyao Wang, Guoyin Wang, Yizhe Zhang, Ricardo Henao, Lawrence Carin:
JointGAN: Multi-Domain Joint Distribution Learning with Generative Adversarial Nets. CoRR abs/1806.02978 (2018) - [i64]Chang Liu, Jingwei Zhuo, Pengyu Cheng, Ruiyi Zhang, Jun Zhu, Lawrence Carin:
Accelerated First-order Methods on the Wasserstein Space for Bayesian Inference. CoRR abs/1807.01750 (2018) - [i63]Ruiyi Zhang, Changyou Chen, Chunyuan Li, Lawrence Carin:
Policy Optimization as Wasserstein Gradient Flows. CoRR abs/1808.03030 (2018) - [i62]Dinghan Shen, Xinyuan Zhang, Ricardo Henao, Lawrence Carin:
Improved Semantic-Aware Network Embedding with Fine-Grained Word Alignment. CoRR abs/1808.09633 (2018) - [i61]Matthew Engelhard, Hongteng Xu, Lawrence Carin, Jason A. Oliver, Matthew Hallyburton, F. Joseph McClernon:
Predicting Smoking Events with a Time-Varying Semi-Parametric Hawkes Process Model. CoRR abs/1809.01740 (2018) - [i60]Bai Li, Changyou Chen, Wenlin Wang, Lawrence Carin:
Second-Order Adversarial Attack and Certifiable Robustness. CoRR abs/1809.03113 (2018) - [i59]Hongteng Xu, Wenlin Wang, Wei Liu, Lawrence Carin:
Distilled Wasserstein Learning for Word Embedding and Topic Modeling. CoRR abs/1809.04705 (2018) - [i58]Liqun Chen, Shuyang Dai, Chenyang Tao, Dinghan Shen, Zhe Gan, Haichao Zhang, Yizhe Zhang, Lawrence Carin:
Adversarial Text Generation via Feature-Mover's Distance. CoRR abs/1809.06297 (2018) - [i57]Ruiyi Zhang, Changyou Chen, Zhe Gan, Wenlin Wang, Liqun Chen, Dinghan Shen, Guoyin Wang, Lawrence Carin:
Sequence Generation with Guider Network. CoRR abs/1811.00696 (2018) - [i56]Kevin J. Liang, Chunyuan Li, Guoyin Wang, Lawrence Carin:
Generative Adversarial Network Training is a Continual Learning Problem. CoRR abs/1811.11083 (2018) - [i55]Zhao Song, Ronald E. Parr, Lawrence Carin:
Revisiting the Softmax Bellman Operator: Theoretical Properties and Practical Benefits. CoRR abs/1812.00456 (2018) - [i54]Yitong Li, Zhe Gan, Yelong Shen, Jingjing Liu, Yu Cheng, Yuexin Wu, Lawrence Carin, David E. Carlson, Jianfeng Gao:
StoryGAN: A Sequential Conditional GAN for Story Visualization. CoRR abs/1812.02784 (2018) - 2017
- [j113]Liming Wang, Minhua Chen, Miguel R. D. Rodrigues, David Wilcox, A. Robert Calderbank, Lawrence Carin:
Information-Theoretic Compressive Measurement Design. IEEE Trans. Pattern Anal. Mach. Intell. 39(6): 1150-1164 (2017) - [j112]Ikenna Odinaka, Joseph A. O'Sullivan, David G. Politte, Kenneth P. MacCabe, Yan Kaganovsky, Joel A. Greenberg, Manu N. Lakshmanan, Kalyani Krishnamurthy, Anuj J. Kapadia, Lawrence Carin, David J. Brady:
Joint System and Algorithm Design for Computationally Efficient Fan Beam Coded Aperture X-Ray Coherent Scatter Imaging. IEEE Trans. Computational Imaging 3(4): 506-521 (2017) - [c189]Qinliang Su, Xuejun Liao, Chunyuan Li, Zhe Gan, Lawrence Carin:
Unsupervised Learning with Truncated Gaussian Graphical Models. AAAI 2017: 2583-2589 - [c188]Zhe Gan, Chunyuan Li, Changyou Chen, Yunchen Pu, Qinliang Su, Lawrence Carin:
Scalable Bayesian Learning of Recurrent Neural Networks for Language Modeling. ACL (1) 2017: 321-331 - [c187]Andrew Stevens, Yunchen Pu, Yannan Sun, Gregory Spell, Lawrence Carin:
Tensor-Dictionary Learning with Deep Kruskal-Factor Analysis. AISTATS 2017: 121-129 - [c186]Shengyang Sun, Changyou Chen, Lawrence Carin:
Learning Structured Weight Uncertainty in Bayesian Neural Networks. AISTATS 2017: 1283-1292 - [c185]Eugenie Komives, Shelley A. Rusincovitch, John Paat, Lawrence Carin, Daniel Costello, Michael Gao, Bradley G. Hammill, Ricardo Henao, Nigel B. Neely, Ursula Rogers, Devdutta Sangvai, Mary Schilder, Erich Huang:
Guiding Principles for the Duke Connected Care Predictive Modeling Pilot. AMIA 2017 - [c184]Shelley A. Rusincovitch, Ricardo Henao, Michael Gao, Lawrence Carin, Ursula Rogers, Nigel B. Neely, Mary Schilder, Daniel Costello, Eugenie Komives, Erich Huang:
Rationale and Design for the Duke Connected Care Predictive Modeling Pilot with a Medicare Shared Savings Program Population. AMIA 2017 - [c183]Zhe Gan, Chuang Gan, Xiaodong He, Yunchen Pu, Kenneth Tran, Jianfeng Gao, Lawrence Carin, Li Deng:
Semantic Compositional Networks for Visual Captioning. CVPR 2017: 1141-1150 - [c182]Zhe Gan, Yunchen Pu, Ricardo Henao, Chunyuan Li, Xiaodong He, Lawrence Carin:
Learning Generic Sentence Representations Using Convolutional Neural Networks. EMNLP 2017: 2390-2400 - [c181]Yunchen Pu, Martin Renqiang Min, Zhe Gan, Lawrence Carin:
Adaptive Feature Abstraction for Translating Video to Language. ICLR (Workshop) 2017 - [c180]Changwei Hu, Piyush Rai, Lawrence Carin:
Deep Generative Models for Relational Data with Side Information. ICML 2017: 1578-1586 - [c179]Yizhe Zhang, Changyou Chen, Zhe Gan, Ricardo Henao, Lawrence Carin:
Stochastic Gradient Monomial Gamma Sampler. ICML 2017: 3996-4005 - [c178]Yizhe Zhang, Zhe Gan, Kai Fan, Zhi Chen, Ricardo Henao, Dinghan Shen, Lawrence Carin:
Adversarial Feature Matching for Text Generation. ICML 2017: 4006-4015 - [c177]Zhengming Xing, Sunshine Hillygus, Lawrence Carin:
Evaluating U.S. Electoral Representation with a Joint Statistical Model of Congressional Roll-Calls, Legislative Text, and Voter Registration Data. KDD 2017: 1205-1214 - [c176]Kai Fan, Qi Wei, Lawrence Carin, Katherine A. Heller:
An inner-loop free solution to inverse problems using deep neural networks. NIPS 2017: 2370-2380 - [c175]Yizhe Zhang, Dinghan Shen, Guoyin Wang, Zhe Gan, Ricardo Henao, Lawrence Carin:
Deconvolutional Paragraph Representation Learning. NIPS 2017: 4169-4179 - [c174]Yunchen Pu, Zhe Gan, Ricardo Henao, Chunyuan Li, Shaobo Han, Lawrence Carin:
VAE Learning via Stein Variational Gradient Descent. NIPS 2017: 4236-4245 - [c173]Yunchen Pu, Weiyao Wang, Ricardo Henao, Liqun Chen, Zhe Gan, Chunyuan Li, Lawrence Carin:
Adversarial Symmetric Variational Autoencoder. NIPS 2017: 4330-4339 - [c172]Qinliang Su, Xuejun Liao, Lawrence Carin:
A Probabilistic Framework for Nonlinearities in Stochastic Neural Networks. NIPS 2017: 4486-4495 - [c171]Zhao Song, Yusuke Muraoka, Ryohei Fujimaki, Lawrence Carin:
Scalable Model Selection for Belief Networks. NIPS 2017: 4609-4619 - [c170]Yitong Li, Michael Murias, Samantha Major, Geraldine Dawson, Kafui Dzirasa, Lawrence Carin, David E. Carlson:
Targeting EEG/LFP Synchrony with Neural Nets. NIPS 2017: 4620-4630 - [c169]Zhe Gan, Liqun Chen, Weiyao Wang, Yunchen Pu, Yizhe Zhang, Hao Liu, Chunyuan Li, Lawrence Carin:
Triangle Generative Adversarial Networks. NIPS 2017: 5247-5256 - [c168]Chunyuan Li, Hao Liu, Changyou Chen, Yunchen Pu, Liqun Chen, Ricardo Henao, Lawrence Carin:
ALICE: Towards Understanding Adversarial Learning for Joint Distribution Matching. NIPS 2017: 5495-5503 - [c167]Neil Gallagher, Kyle R. Ulrich, Austin Talbot, Kafui Dzirasa, Lawrence Carin, David E. Carlson:
Cross-Spectral Factor Analysis. NIPS 2017: 6842-6852 - [i53]Xin Yuan, Yunchen Pu, Lawrence Carin:
Compressive Sensing via Convolutional Factor Analysis. CoRR abs/1701.03006 (2017) - [i52]Yunchen Pu, Zhe Gan, Ricardo Henao, Chunyuan Li, Shaobo Han, Lawrence Carin:
Stein Variational Autoencoder. CoRR abs/1704.05155 (2017) - [i51]Yizhe Zhang, Changyou Chen, Zhe Gan, Ricardo Henao, Lawrence Carin:
Stochastic Gradient Monomial Gamma Sampler. CoRR abs/1706.01498 (2017) - [i50]Yizhe Zhang, Zhe Gan, Kai Fan, Zhi Chen, Ricardo Henao, Dinghan Shen, Lawrence Carin:
Adversarial Feature Matching for Text Generation. CoRR abs/1706.03850 (2017) - [i49]Yizhe Zhang, Dinghan Shen, Guoyin Wang, Zhe Gan, Ricardo Henao, Lawrence Carin:
Deconvolutional Paragraph Representation Learning. CoRR abs/1708.04729 (2017) - [i48]Chunyuan Li, Hao Liu, Changyou Chen, Yunchen Pu, Liqun Chen, Ricardo Henao, Lawrence Carin:
Towards Understanding Adversarial Learning for Joint Distribution Matching. CoRR abs/1709.01215 (2017) - [i47]Qi Wei, Kai Fan, Lawrence Carin, Katherine A. Heller:
An inner-loop free solution to inverse problems using deep neural networks. CoRR abs/1709.01841 (2017) - [i46]Yunchen Pu, Liqun Chen, Shuyang Dai, Weiyao Wang, Chunyuan Li, Lawrence Carin:
Symmetric Variational Autoencoder and Connections to Adversarial Learning. CoRR abs/1709.01846 (2017) - [i45]Qinliang Su, Xuejun Liao, Lawrence Carin:
A Probabilistic Framework for Nonlinearities in Stochastic Neural Networks. CoRR abs/1709.06123 (2017) - [i44]Zhe Gan, Liqun Chen, Weiyao Wang, Yunchen Pu, Yizhe Zhang, Hao Liu, Chunyuan Li, Lawrence Carin:
Triangle Generative Adversarial Networks. CoRR abs/1709.06548 (2017) - [i43]Dinghan Shen, Yizhe Zhang, Ricardo Henao, Qinliang Su, Lawrence Carin:
Deconvolutional Latent-Variable Model for Text Sequence Matching. CoRR abs/1709.07109 (2017) - [i42]Dinghan Shen, Martin Renqiang Min, Yitong Li, Lawrence Carin:
Adaptive Convolutional Filter Generation for Natural Language Understanding. CoRR abs/1709.08294 (2017) - [i41]Yitong Li, Martin Renqiang Min, Dinghan Shen, David E. Carlson, Lawrence Carin:
Video Generation From Text. CoRR abs/1710.00421 (2017) - [i40]Yunchen Pu, Weiyao Wang, Ricardo Henao, Liqun Chen, Zhe Gan, Chunyuan Li, Lawrence Carin:
Adversarial Symmetric Variational Autoencoder. CoRR abs/1711.04915 (2017) - [i39]Wenlin Wang, Yunchen Pu, Vinay Kumar Verma, Kai Fan, Yizhe Zhang, Changyou Chen, Piyush Rai, Lawrence Carin:
Zero-Shot Learning via Class-Conditioned Deep Generative Models. CoRR abs/1711.05820 (2017) - [i38]Bai Li, Changyou Chen, Hao Liu, Lawrence Carin:
On Connecting Stochastic Gradient MCMC and Differential Privacy. CoRR abs/1712.09097 (2017) - [i37]Wenlin Wang, Zhe Gan, Wenqi Wang, Dinghan Shen, Jiaji Huang, Wei Ping, Sanjeev Satheesh, Lawrence Carin:
Topic Compositional Neural Language Model. CoRR abs/1712.09783 (2017) - 2016
- [j111]Ricardo Henao, James Lu, Joseph E. Lucas, Jeffrey M. Ferranti, Lawrence Carin:
Electronic Health Record Analysis via Deep Poisson Factor Models. J. Mach. Learn. Res. 17: 186:1-186:32 (2016) - [j110]David E. Carlson, Ya-Ping Hsieh, Edo Collins, Lawrence Carin, Volkan Cevher:
Stochastic Spectral Descent for Discrete Graphical Models. IEEE J. Sel. Top. Signal Process. 10(2): 296-311 (2016) - [j109]Xun Cao, Tao Yue, Xing Lin, Stephen Lin, Xin Yuan, Qionghai Dai, Lawrence Carin, David J. Brady:
Computational Snapshot Multispectral Cameras: Toward dynamic capture of the spectral world. IEEE Signal Process. Mag. 33(5): 95-108 (2016) - [j108]Francesco Renna, Liming Wang, Xin Yuan, Jianbo Yang, Galen Reeves, A. Robert Calderbank, Lawrence Carin, Miguel R. D. Rodrigues:
Classification and Reconstruction of High-Dimensional Signals From Low-Dimensional Features in the Presence of Side Information. IEEE Trans. Inf. Theory 62(11): 6459-6492 (2016) - [c166]Yizhe Zhang, Ricardo Henao, Lawrence Carin, Jianling Zhong, Alexander J. Hartemink:
Learning a Hybrid Architecture for Sequence Regression and Annotation. AAAI 2016: 1415-1421 - [c165]Chunyuan Li, Changyou Chen, David E. Carlson, Lawrence Carin:
Preconditioned Stochastic Gradient Langevin Dynamics for Deep Neural Networks. AAAI 2016: 1788-1794 - [c164]Chunyuan Li, Changyou Chen, Kai Fan, Lawrence Carin:
High-Order Stochastic Gradient Thermostats for Bayesian Learning of Deep Models. AAAI 2016: 1795-1801 - [c163]Zhao Song, Xuejun Liao, Lawrence Carin:
Solving DEC-POMDPs by Expectation Maximization of Value Function. AAAI Spring Symposia 2016 - [c162]Yunchen Pu, Xin Yuan, Andrew Stevens, Chunyuan Li, Lawrence Carin:
A Deep Generative Deconvolutional Image Model. AISTATS 2016: 741-750 - [c161]Shaobo Han, Xuejun Liao, David B. Dunson, Lawrence Carin:
Variational Gaussian Copula Inference. AISTATS 2016: 829-838 - [c160]Changyou Chen, David E. Carlson, Zhe Gan, Chunyuan Li, Lawrence Carin:
Bridging the Gap between Stochastic Gradient MCMC and Stochastic Optimization. AISTATS 2016: 1051-1060 - [c159]Changwei Hu, Piyush Rai, Lawrence Carin:
Non-negative Matrix Factorization for Discrete Data with Hierarchical Side-Information. AISTATS 2016: 1124-1132 - [c158]Changwei Hu, Piyush Rai, Lawrence Carin:
Topic-Based Embeddings for Learning from Large Knowledge Graphs. AISTATS 2016: 1133-1141 - [c157]Zhao Song, Ricardo Henao, David E. Carlson, Lawrence Carin:
Learning Sigmoid Belief Networks via Monte Carlo Expectation Maximization. AISTATS 2016: 1347-1355 - [c156]Yan Kaganovsky, Ikenna Odinaka, David E. Carlson, Lawrence Carin:
Parallel Majorization Minimization with Dynamically Restricted Domains for Nonconvex Optimization. AISTATS 2016: 1497-1505 - [c155]Chunyuan Li, Andrew Stevens, Changyou Chen, Yunchen Pu, Zhe Gan, Lawrence Carin:
Learning Weight Uncertainty with Stochastic Gradient MCMC for Shape Classification. CVPR 2016: 5666-5675 - [c154]Liming Wang, Francesco Renna, Xin Yuan, Miguel R. D. Rodrigues, A. Robert Calderbank, Lawrence Carin:
A general framework for reconstruction and classification from compressive measurements with side information. ICASSP 2016: 4239-4243 - [c153]Yizhe Zhang, Yue Zhao, Lawrence David, Ricardo Henao, Lawrence Carin:
Dynamic Poisson Factor Analysis. ICDM 2016: 1359-1364 - [c152]Jiaming Song, Zhe Gan, Lawrence Carin:
Factored Temporal Sigmoid Belief Networks for Sequence Learning. ICML 2016: 1272-1281 - [c151]Qinliang Su, Xuejun Liao, Changyou Chen, Lawrence Carin:
Nonlinear Statistical Learning with Truncated Gaussian Graphical Models. ICML 2016: 1948-1957 - [c150]Yizhe Zhang, Ricardo Henao, Chunyuan Li, Lawrence Carin:
Bayesian Dictionary Learning with Gaussian Processes and Sigmoid Belief Networks. IJCAI 2016: 2364-2370 - [c149]Yizhe Zhang, Xiangyu Wang, Changyou Chen, Ricardo Henao, Kai Fan, Lawrence Carin:
Towards Unifying Hamiltonian Monte Carlo and Slice Sampling. NIPS 2016: 1741-1749 - [c148]Yunchen Pu, Zhe Gan, Ricardo Henao, Xin Yuan, Chunyuan Li, Andrew Stevens, Lawrence Carin:
Variational Autoencoder for Deep Learning of Images, Labels and Captions. NIPS 2016: 2352-2360 - [c147]Changyou Chen, Nan Ding, Chunyuan Li, Yizhe Zhang, Lawrence Carin:
Stochastic Gradient MCMC with Stale Gradients. NIPS 2016: 2937-2945 - [c146]Zhao Song, Ronald E. Parr, Xuejun Liao, Lawrence Carin:
Linear Feature Encoding for Reinforcement Learning. NIPS 2016: 4224-4232 - [c145]Yizhe Zhang, Changyou Chen, Ricardo Henao, Lawrence Carin:
Laplacian Hamiltonian Monte Carlo. ECML/PKDD (1) 2016: 98-114 - [c144]Wenlin Wang, Changyou Chen, Wenlin Chen, Piyush Rai, Lawrence Carin:
Deep Metric Learning with Data Summarization. ECML/PKDD (1) 2016: 777-794 - [p1]Zhe Gan, Xin Yuan, Ricardo Henao, Ephraim L. Tsalik, Lawrence Carin:
Inference of gene networks associated with the host response to infectious disease. Big Data over Networks 2016: 365-390 - [i36]Ikenna Odinaka, Yan Kaganovsky, Joel A. Greenberg, Mehadi Hassan, David G. Politte, Joseph A. O'Sullivan, Lawrence Carin, David J. Brady:
Spectrally Grouped Total Variation Reconstruction for Scatter Imaging Using ADMM. CoRR abs/1601.08201 (2016) - [i35]Ikenna Odinaka, Joseph A. O'Sullivan, David G. Politte, Kenneth P. MacCabe, Yan Kaganovsky, Joel A. Greenberg, Manu N. Lakshmanan, Kalyani Krishnamurthy, Anuj J. Kapadia, Lawrence Carin, David J. Brady:
Joint System and Algorithm Design for Computationally Efficient Fan Beam Coded Aperture X-ray Coherent Scatter Imaging. CoRR abs/1603.06400 (2016) - [i34]Jiaming Song, Zhe Gan, Lawrence Carin:
Factored Temporal Sigmoid Belief Networks for Sequence Learning. CoRR abs/1605.06715 (2016) - [i33]Yunchen Pu, Zhe Gan, Ricardo Henao, Xin Yuan, Chunyuan Li, Andrew Stevens, Lawrence Carin:
Variational Autoencoder for Deep Learning of Images, Labels and Captions. CoRR abs/1609.08976 (2016) - [i32]Changyou Chen, Nan Ding, Chunyuan Li, Yizhe Zhang, Lawrence Carin:
Stochastic Gradient MCMC with Stale Gradients. CoRR abs/1610.06664 (2016) - [i31]Wenlin Wang, Changyou Chen, Wenqi Wang, Piyush Rai, Lawrence Carin:
Earliness-Aware Deep Convolutional Networks for Early Time Series Classification. CoRR abs/1611.04578 (2016) - [i30]Qinliang Su, Xuejun Liao, Chunyuan Li, Zhe Gan, Lawrence Carin:
Unsupervised Learning with Truncated Gaussian Graphical Models. CoRR abs/1611.04920 (2016) - [i29]Yunchen Pu, Martin Renqiang Min, Zhe Gan, Lawrence Carin:
Adaptive Feature Abstraction for Translating Video to Language. CoRR abs/1611.07837 (2016) - [i28]Zhe Gan, Yunchen Pu, Ricardo Henao, Chunyuan Li, Xiaodong He, Lawrence Carin:
Unsupervised Learning of Sentence Representations using Convolutional Neural Networks. CoRR abs/1611.07897 (2016) - [i27]Zhe Gan, Chuang Gan, Xiaodong He, Yunchen Pu, Kenneth Tran, Jianfeng Gao, Lawrence Carin, Li Deng:
Semantic Compositional Networks for Visual Captioning. CoRR abs/1611.08002 (2016) - [i26]Zhe Gan, Chunyuan Li, Changyou Chen, Yunchen Pu, Qinliang Su, Lawrence Carin:
Scalable Bayesian Learning of Recurrent Neural Networks for Language Modeling. CoRR abs/1611.08034 (2016) - [i25]Andrew Stevens, Yunchen Pu, Yannan Sun, Gregory Spell, Lawrence Carin:
Deep Overcomplete Tensor Rank-Decompositions. CoRR abs/1612.02842 (2016) - 2015
- [j107]Xin Yuan, Tsung-Han Tsai, Ruoyu Zhu, Patrick Llull, David J. Brady, Lawrence Carin:
Compressive Hyperspectral Imaging With Side Information. IEEE J. Sel. Top. Signal Process. 9(6): 964-976 (2015) - [j106]Yanbin Lu, Lawrence Carin, Ronald R. Coifman, William Shain, Badrinath Roysam:
Quantitative Arbor Analytics: Unsupervised Harmonic Co-Clustering of Populations of Brain Cell Arbors Based on L-Measure. Neuroinformatics 13(1): 47-63 (2015) - [j105]Mingyuan Zhou, Lawrence Carin:
Negative Binomial Process Count and Mixture Modeling. IEEE Trans. Pattern Anal. Mach. Intell. 37(2): 307-320 (2015) - [j104]Gungor Polatkan, Mingyuan Zhou, Lawrence Carin, David M. Blei, Ingrid Daubechies:
A Bayesian Nonparametric Approach to Image Super-Resolution. IEEE Trans. Pattern Anal. Mach. Intell. 37(2): 346-358 (2015) - [j103]Liming Wang, Jiaji Huang, Xin Yuan, Kalyani Krishnamurthy, Joel A. Greenberg, Volkan Cevher, Miguel R. D. Rodrigues, David J. Brady, A. Robert Calderbank, Lawrence Carin:
Signal Recovery and System Calibration from Multiple Compressive Poisson Measurements. SIAM J. Imaging Sci. 8(3): 1923-1954 (2015) - [j102]Yan Kaganovsky, Shaobo Han, Soysal Degirmenci, David G. Politte, David J. Brady, Joseph A. O'Sullivan, Lawrence Carin:
Alternating Minimization Algorithm with Automatic Relevance Determination for Transmission Tomography under Poisson Noise. SIAM J. Imaging Sci. 8(3): 2087-2132 (2015) - [j101]Wenzhao Lian, Ronen Talmon, Hitten Zaveri, Lawrence Carin, Ronald R. Coifman:
Multivariate time-series analysis and diffusion maps. Signal Process. 116: 13-28 (2015) - [j100]Jianbo Yang, Xuejun Liao, Xin Yuan, Patrick Llull, David J. Brady, Guillermo Sapiro, Lawrence Carin:
Compressive Sensing by Learning a Gaussian Mixture Model From Measurements. IEEE Trans. Image Process. 24(1): 106-119 (2015) - [c143]Wenzhao Lian, Piyush Rai, Esther Salazar, Lawrence Carin:
Integrating Features and Similarities: Flexible Models for Heterogeneous Multiview Data. AAAI 2015: 2757-2763 - [c142]Piyush Rai, Yingjian Wang, Lawrence Carin:
Leveraging Features and Networks for Probabilistic Tensor Decomposition. AAAI 2015: 2942-2948 - [c141]Yi Zhen, Piyush Rai, Hongyuan Zha, Lawrence Carin:
Cross-Modal Similarity Learning via Pairs, Preferences, and Active Supervision. AAAI 2015: 3203-3209 - [c140]David E. Carlson, Volkan Cevher, Lawrence Carin:
Stochastic Spectral Descent for Restricted Boltzmann Machines. AISTATS 2015 - [c139]Zhe Gan, Ricardo Henao, David E. Carlson, Lawrence Carin:
Learning Deep Sigmoid Belief Networks with Data Augmentation. AISTATS 2015 - [c138]Xin Yuan, Ricardo Henao, Ephraim Tsalik, Raymond Langley, Lawrence Carin:
Non-Gaussian Discriminative Factor Models via the Max-Margin Rank-Likelihood. ICML 2015: 1254-1263 - [c137]Zhe Gan, Changyou Chen, Ricardo Henao, David E. Carlson, Lawrence Carin:
Scalable Deep Poisson Factor Analysis for Topic Modeling. ICML 2015: 1823-1832 - [c136]Wenzhao Lian, Ricardo Henao, Vinayak A. Rao, Joseph E. Lucas, Lawrence Carin:
A Multitask Point Process Predictive Model. ICML 2015: 2030-2038 - [c135]Miao Liu, Christopher Amato, Xuejun Liao, Lawrence Carin, Jonathan P. How:
Stick-Breaking Policy Learning in Dec-POMDPs. IJCAI 2015: 2011-2018 - [c134]Piyush Rai, Changwei Hu, Matthew Harding, Lawrence Carin:
Scalable Probabilistic Tensor Factorization for Binary and Count Data. IJCAI 2015: 3770-3776 - [c133]Francesco Renna, Liming Wang, Xin Yuan, Jianbo Yang, Galen Reeves, A. Robert Calderbank, Lawrence Carin, Miguel R. D. Rodrigues:
Classification and reconstruction of compressed GMM signals with side information. ISIT 2015: 994-998 - [c132]Liming Wang, Jiaji Huang, Xin Yuan, Volkan Cevher, Miguel R. D. Rodrigues, A. Robert Calderbank, Lawrence Carin:
A concentration-of-measure inequality for multiple-measurement models. ISIT 2015: 2341-2345 - [c131]Yan Kaganovsky, Soysal Degirmenci, Shaobo Han, Ikenna Odinaka, David G. Politte, David J. Brady, Joseph A. O'Sullivan, Lawrence Carin:
Alternating minimization algorithm with iteratively reweighted quadratic penalties for compressive transmission tomography. Image Processing 2015: 94130J - [c130]Kyle R. Ulrich, David E. Carlson, Kafui Dzirasa, Lawrence Carin:
GP Kernels for Cross-Spectrum Analysis. NIPS 2015: 1999-2007 - [c129]Changyou Chen, Nan Ding, Lawrence Carin:
On the Convergence of Stochastic Gradient MCMC Algorithms with High-Order Integrators. NIPS 2015: 2278-2286 - [c128]Zhe Gan, Chunyuan Li, Ricardo Henao, David E. Carlson, Lawrence Carin:
Deep Temporal Sigmoid Belief Networks for Sequence Modeling. NIPS 2015: 2467-2475 - [c127]Ricardo Henao, Zhe Gan, James Lu, Lawrence Carin:
Deep Poisson Factor Modeling. NIPS 2015: 2800-2808 - [c126]David E. Carlson, Edo Collins, Ya-Ping Hsieh, Lawrence Carin, Volkan Cevher:
Preconditioned Spectral Descent for Deep Learning. NIPS 2015: 2971-2979 - [c125]Piyush Rai, Changwei Hu, Ricardo Henao, Lawrence Carin:
Large-Scale Bayesian Multi-Label Learning via Topic-Based Label Embeddings. NIPS 2015: 3222-3230 - [c124]Changwei Hu, Piyush Rai, Changyou Chen, Matthew Harding, Lawrence Carin:
Scalable Bayesian Non-negative Tensor Factorization for Massive Count Data. ECML/PKDD (2) 2015: 53-70 - [c123]Changwei Hu, Piyush Rai, Lawrence Carin:
Zero-Truncated Poisson Tensor Factorization for Massive Binary Tensors. UAI 2015: 375-384 - [c122]Yunchen Pu, Xin Yuan, Lawrence Carin:
A Generative Model for Deep Convolutional Learning. ICLR (Workshop) 2015 - [i24]Xin Yuan, Tsung-Han Tsai, Ruoyu Zhu, Patrick Llull, David J. Brady, Lawrence Carin:
Compressive Hyperspectral Imaging with Side Information. CoRR abs/1502.06260 (2015) - [i23]Miao Liu, Christopher Amato, Xuejun Liao, Lawrence Carin, Jonathan P. How:
Stick-Breaking Policy Learning in Dec-POMDPs. CoRR abs/1505.00274 (2015) - [i22]Shaobo Han, Xuejun Liao, David B. Dunson, Lawrence Carin:
Variational Gaussian Copula Inference. CoRR abs/1506.05860 (2015) - [i21]Changwei Hu, Piyush Rai, Lawrence Carin:
Zero-Truncated Poisson Tensor Factorization for Massive Binary Tensors. CoRR abs/1508.04210 (2015) - [i20]Changwei Hu, Piyush Rai, Changyou Chen, Matthew Harding, Lawrence Carin:
Scalable Bayesian Non-Negative Tensor Factorization for Massive Count Data. CoRR abs/1508.04211 (2015) - [i19]Zhe Gan, Chunyuan Li, Ricardo Henao, David E. Carlson, Lawrence Carin:
Deep Temporal Sigmoid Belief Networks for Sequence Modeling. CoRR abs/1509.07087 (2015) - [i18]Yunchen Pu, Xin Yuan, Andrew Stevens, Chunyuan Li, Lawrence Carin:
A Deep Generative Deconvolutional Image Model. CoRR abs/1512.07344 (2015) - [i17]Changyou Chen, David E. Carlson, Zhe Gan, Chunyuan Li, Lawrence Carin:
Bridging the Gap between Stochastic Gradient MCMC and Stochastic Optimization. CoRR abs/1512.07962 (2015) - 2014
- [j99]Priyadip Ray, Lingling Zheng, Joseph E. Lucas, Lawrence Carin:
Bayesian joint analysis of heterogeneous genomics data. Bioinform. 30(10): 1370-1376 (2014) - [j98]Xuejun Liao, Hui Li, Lawrence Carin:
Generalized Alternating Projection for Weighted-퓁2, 1 Minimization with Applications to Model-Based Compressive Sensing. SIAM J. Imaging Sci. 7(2): 797-823 (2014) - [j97]Gonzalo R. Arce, David J. Brady, Lawrence Carin, Henry Arguello, David S. Kittle:
Compressive Coded Aperture Spectral Imaging: An Introduction. IEEE Signal Process. Mag. 31(1): 105-115 (2014) - [j96]David E. Carlson, Joshua T. Vogelstein, Qisong Wu, Wenzhao Lian, Mingyuan Zhou, Colin R. Stoetzner, Daryl Kipke, Douglas Weber, David B. Dunson, Lawrence Carin:
Multichannel Electrophysiological Spike Sorting via Joint Dictionary Learning and Mixture Modeling. IEEE Trans. Biomed. Eng. 61(1): 41-54 (2014) - [j95]Jianbo Yang, Xin Yuan, Xuejun Liao, Patrick Llull, David J. Brady, Guillermo Sapiro, Lawrence Carin:
Video Compressive Sensing Using Gaussian Mixture Models. IEEE Trans. Image Process. 23(11): 4863-4878 (2014) - [j94]Liming Wang, David Edwin Carlson, Miguel R. D. Rodrigues, A. Robert Calderbank, Lawrence Carin:
A Bregman Matrix and the Gradient of Mutual Information for Vector Poisson and Gaussian Channels. IEEE Trans. Inf. Theory 60(5): 2611-2629 (2014) - [j93]Francesco Renna, A. Robert Calderbank, Lawrence Carin, Miguel R. D. Rodrigues:
Reconstruction of Signals Drawn From a Gaussian Mixture Via Noisy Compressive Measurements. IEEE Trans. Signal Process. 62(9): 2265-2277 (2014) - [j92]Xin Yuan, Vinayak A. Rao, Shaobo Han, Lawrence Carin:
Hierarchical Infinite Divisibility for Multiscale Shrinkage. IEEE Trans. Signal Process. 62(17): 4363-4374 (2014) - [c121]Changwei Hu, Eunsu Ryu, David E. Carlson, Yingjian Wang, Lawrence Carin:
Latent Gaussian Models for Topic Modeling. AISTATS 2014: 393-401 - [c120]Haichao Zhang, Lawrence Carin:
Multi-shot Imaging: Joint Alignment, Deblurring, and Resolution-Enhancement. CVPR 2014: 2925-2932 - [c119]Xin Yuan, Patrick Llull, Xuejun Liao, Jianbo Yang, David J. Brady, Guillermo Sapiro, Lawrence Carin:
Low-Cost Compressive Sensing for Color Video and Depth. CVPR 2014: 3318-3325 - [c118]Wenzhao Lian, Vinayak A. Rao, Brian Eriksson, Lawrence Carin:
Modeling Correlated Arrival Events with Latent Semi-Markov Processes. ICML 2014: 396-404 - [c117]Liming Wang, Abolfazl Razi, Miguel R. D. Rodrigues, A. Robert Calderbank, Lawrence Carin:
Nonlinear Information-Theoretic Compressive Measurement Design. ICML 2014: 1161-1169 - [c116]Piyush Rai, Yingjian Wang, Shengbo Guo, Gary Chen, David B. Dunson, Lawrence Carin:
Scalable Bayesian Low-Rank Decomposition of Incomplete Multiway Tensors. ICML 2014: 1800-1808 - [c115]Ricardo Henao, Xin Yuan, Lawrence Carin:
Bayesian Nonlinear Support Vector Machines and Discriminative Factor Modeling. NIPS 2014: 1754-1762 - [c114]David E. Carlson, Jana Schaich Borg, Kafui Dzirasa, Lawrence Carin:
On the relations of LFPs & Neural Spike Trains. NIPS 2014: 2060-2068 - [c113]Kyle R. Ulrich, David E. Carlson, Wenzhao Lian, Jana Schaich Borg, Kafui Dzirasa, Lawrence Carin:
Analysis of Brain States from Multi-Region LFP Time-Series. NIPS 2014: 2483-2491 - [c112]Shaobo Han, Lin Du, Esther Salazar, Lawrence Carin:
Dynamic Rank Factor Model for Text Streams. NIPS 2014: 2663-2671 - [c111]Jianbo Yang, Xuejun Liao, Minhua Chen, Lawrence Carin:
Compressive Sensing of Signals from a GMM with Sparse Precision Matrices. NIPS 2014: 3194-3202 - [i16]Xin Yuan, Patrick Llull, Xuejun Liao, Jianbo Yang, Guillermo Sapiro, David J. Brady, Lawrence Carin:
Low-Cost Compressive Sensing for Color Video and Depth. CoRR abs/1402.6932 (2014) - [i15]Xin Yuan, Patrick Llull, David J. Brady, Lawrence Carin:
Tree-Structure Bayesian Compressive Sensing for Video. CoRR abs/1410.3080 (2014) - [i14]Francesco Renna, Liming Wang, Xin Yuan, Jianbo Yang, Galen Reeves, A. Robert Calderbank, Lawrence Carin, Miguel R. D. Rodrigues:
Classification and Reconstruction of High-Dimensional Signals from Low-Dimensional Noisy Features in the Presence of Side Information. CoRR abs/1412.0614 (2014) - [i13]Yunchen Pu, Xin Yuan, Lawrence Carin:
Bayesian Deep Deconvolutional Learning. CoRR abs/1412.6039 (2014) - 2013
- [j91]Esther Salazar, David B. Dunson, Lawrence Carin:
Analysis of space-time relational data with application to legislative voting. Comput. Stat. Data Anal. 68: 141-154 (2013) - [j90]Bo Chen, Gungor Polatkan, Guillermo Sapiro, David M. Blei, David B. Dunson, Lawrence Carin:
Deep Learning with Hierarchical Convolutional Factor Analysis. IEEE Trans. Pattern Anal. Mach. Intell. 35(8): 1887-1901 (2013) - [j89]Ajit Rajwade, David S. Kittle, Tsung-Han Tsai, David J. Brady, Lawrence Carin:
Coded Hyperspectral Imaging and Blind Compressive Sensing. SIAM J. Imaging Sci. 6(2): 782-812 (2013) - [j88]Julio Martin Duarte-Carvajalino, Guoshen Yu, Lawrence Carin, Guillermo Sapiro:
Task-Driven Adaptive Statistical Compressive Sensing of Gaussian Mixture Models. IEEE Trans. Signal Process. 61(3): 585-600 (2013) - [c110]Ricardo Henao, Jared Murray, Geoffrey S. Ginsburg, Lawrence Carin, Joseph E. Lucas:
Patient Clustering with Uncoded Text in Electronic Medical Records. AMIA 2013 - [c109]Divyanshu Vats, Christoph Studer, Andrew S. Lan, Lawrence Carin, Richard G. Baraniuk:
Test-size Reduction for Concept Estimation. EDM 2013: 292-295 - [c108]Francesco Renna, A. Robert Calderbank, Lawrence Carin, Miguel R. D. Rodrigues:
Reconstruction of Gaussian mixture models from compressive measurements: A phase transition view. GlobalSIP 2013: 628 - [c107]Francesco Renna, Miguel R. D. Rodrigues, Minhua Chen, A. Robert Calderbank, Lawrence Carin:
Compressive sensing for incoherent imaging systems with optical constraints. ICASSP 2013: 5484-5488 - [c106]Xin Yuan, Jianbo Yang, Patrick Llull, Xuejun Liao, Guillermo Sapiro, David J. Brady, Lawrence Carin:
Adaptive temporal compressive sensing for video. ICIP 2013: 14-18 - [c105]Jianbo Yang, Xin Yuan, Xuejun Liao, Patrick Llull, Guillermo Sapiro, David J. Brady, Lawrence Carin:
Gaussian mixture model for video compressive sensing. ICIP 2013: 19-23 - [c104]Esther Salazar, Ryan Bogdan, Adam Gorka, Ahmad Hariri, Lawrence Carin:
Exploring the Mind: Integrating Questionnaires and fMRI. ICML (2) 2013: 262-270 - [c103]Miao Liu, Xuejun Liao, Lawrence Carin:
Online Expectation Maximization for Reinforcement Learning in POMDPs. IJCAI 2013: 1501-1507 - [c102]Yanbin Lu, Kristen Trett, William Shain, Lawrence Carin, Ronald R. Coifman, Badrinath Roysam:
Quantitative profiling of microglia populations using harmonic co-clustering of arbor morphology measurements. ISBI 2013: 1360-1363 - [c101]Liming Wang, Miguel R. D. Rodrigues, Lawrence Carin:
Generalized Bregman divergence and gradient of mutual information for vector Poisson channels. ISIT 2013: 454-458 - [c100]Trevor Campbell, Miao Liu, Brian Kulis, Jonathan P. How, Lawrence Carin:
Dynamic Clustering via Asymptotics of the Dependent Dirichlet Process Mixture. NIPS 2013: 449-457 - [c99]Liming Wang, David E. Carlson, Miguel R. D. Rodrigues, David Wilcox, A. Robert Calderbank, Lawrence Carin:
Designed Measurements for Vector Count Data. NIPS 2013: 1142-1150 - [c98]Shaobo Han, Xuejun Liao, Lawrence Carin:
Integrated Non-Factorized Variational Inference. NIPS 2013: 2481-2489 - [c97]David E. Carlson, Vinayak A. Rao, Joshua T. Vogelstein, Lawrence Carin:
Real-Time Inference for a Gamma Process Model of Neural Spiking. NIPS 2013: 2805-2813 - [i12]Liming Wang, Miguel R. D. Rodrigues, Lawrence Carin:
Generalized Bregman Divergence and Gradient of Mutual Information for Vector Poisson Channels. CoRR abs/1301.6648 (2013) - [i11]Patrick Llull, Xuejun Liao, Xin Yuan, Jianbo Yang, David S. Kittle, Lawrence Carin, Guillermo Sapiro, David J. Brady:
Coded aperture compressive temporal imaging. CoRR abs/1302.2575 (2013) - [i10]Xin Yuan, Jianbo Yang, Patrick Llull, Xuejun Liao, Guillermo Sapiro, David J. Brady, Lawrence Carin:
Adaptive Temporal Compressive Sensing for Video. CoRR abs/1302.3446 (2013) - [i9]Francesco Renna, A. Robert Calderbank, Lawrence Carin, Miguel R. D. Rodrigues:
Reconstruction of Signals Drawn from a Gaussian Mixture from Noisy Compressive Measurements: MMSE Phase Transitions and Beyond. CoRR abs/1307.0861 (2013) - 2012
- [j87]Zhengming Xing, Mingyuan Zhou, Alexey Castrodad, Guillermo Sapiro, Lawrence Carin:
Dictionary Learning for Noisy and Incomplete Hyperspectral Images. SIAM J. Imaging Sci. 5(1): 33-56 (2012) - [j86]William R. Carson, Minhua Chen, Miguel R. D. Rodrigues, A. Robert Calderbank, Lawrence Carin:
Communications-Inspired Projection Design with Application to Compressive Sensing. SIAM J. Imaging Sci. 5(4): 1185-1212 (2012) - [j85]Lawrence Carin, Alfred O. Hero III, Joseph E. Lucas, David B. Dunson, Minhua Chen, Ricardo Henao, Arnau Tibau Puig, Aimee K. Zaas, Christopher W. Woods, Geoffrey S. Ginsburg:
High Dimensional Longitudinal Genomic Data: An analysis used for monitoring viral infections. IEEE Signal Process. Mag. 29(1): 108-123 (2012) - [j84]Mingyuan Zhou, Haojun Chen, John W. Paisley, Lu Ren, Lingbo Li, Zhengming Xing, David B. Dunson, Guillermo Sapiro, Lawrence Carin:
Nonparametric Bayesian Dictionary Learning for Analysis of Noisy and Incomplete Images. IEEE Trans. Image Process. 21(1): 130-144 (2012) - [c96]William R. Carson, Miguel R. D. Rodrigues, Minhua Chen, Lawrence Carin, A. Robert Calderbank:
How to focus the discriminative power of a dictionary. ICASSP 2012: 1365-1368 - [c95]Lingbo Li, Jorge G. Silva, Mingyuan Zhou, Lawrence Carin:
Online Bayesian dictionary learning for large datasets. ICASSP 2012: 2157-2160 - [c94]Julio Martin Duarte-Carvajalino, Guoshen Yu, Lawrence Carin, Guillermo Sapiro:
Adapted statistical compressive sensing: Learning to sense gaussian mixture models. ICASSP 2012: 3653-3656 - [c93]Ricardo Henao, J. Will Thompson, M. Arthur Moseley, Geoffrey S. Ginsburg, Lawrence Carin, Joseph E. Lucas:
Hierarchical factor modeling of proteomics data. ICCABS 2012: 1-6 - [c92]Minhua Chen, William R. Carson, Miguel R. D. Rodrigues, Lawrence Carin, A. Robert Calderbank:
Communications Inspired Linear Discriminant Analysis. ICML 2012 - [c91]Shaobo Han, Xuejun Liao, Lawrence Carin:
Cross-Domain Multitask Learning with Latent Probit Models. ICML 2012 - [c90]Esther Salazar, Lawrence Carin:
Inferring Latent Structure From Mixed Real and Categorical Relational Data. ICML 2012 - [c89]Yingjian Wang, Lawrence Carin:
Levy Measure Decompositions for the Beta and Gamma Processes. ICML 2012 - [c88]Mingyuan Zhou, Lingbo Li, David B. Dunson, Lawrence Carin:
Lognormal and Gamma Mixed Negative Binomial Regression. ICML 2012 - [c87]Xu Chen, Mingyuan Zhou, Lawrence Carin:
The contextual focused topic model. KDD 2012: 96-104 - [c86]Jorge G. Silva, Lawrence Carin:
Active learning for online bayesian matrix factorization. KDD 2012: 325-333 - [c85]XianXing Zhang, Lawrence Carin:
Joint Modeling of a Matrix with Associated Text via Latent Binary Features. NIPS 2012: 1565-1573 - [c84]Mingyuan Zhou, Lawrence Carin:
Augment-and-Conquer Negative Binomial Processes. NIPS 2012: 2555-2563 - [c83]Jorge G. Silva, Lawrence Carin:
Active learning for large-scale factor analysis. SSP 2012: 161-164 - [c82]Lingbo Li, XianXing Zhang, Mingyuan Zhou, Lawrence Carin:
Nested Dictionary Learning for Hierarchical Organization of Imagery and Text. UAI 2012: 469-478 - [c81]Mingyuan Zhou, Lauren Hannah, David B. Dunson, Lawrence Carin:
Beta-Negative Binomial Process and Poisson Factor Analysis. AISTATS 2012: 1462-1471 - [i8]Julio Martin Duarte-Carvajalino, Guoshen Yu, Lawrence Carin, Guillermo Sapiro:
Task-Driven Adaptive Statistical Compressive Sensing of Gaussian Mixture Models. CoRR abs/1201.5404 (2012) - [i7]William R. Carson, Minhua Chen, Miguel R. D. Rodrigues, A. Robert Calderbank, Lawrence Carin:
Communications-Inspired Projection Design with Application to Compressive Sensing. CoRR abs/1206.1973 (2012) - [i6]Yingjian Wang, Lawrence Carin:
Levy Measure Decompositions for the Beta and Gamma Processes. CoRR abs/1206.4615 (2012) - [i5]Mingyuan Zhou, Lingbo Li, David B. Dunson, Lawrence Carin:
Lognormal and Gamma Mixed Negative Binomial Regression. CoRR abs/1206.6456 (2012) - [i4]Gungor Polatkan, Mingyuan Zhou, Lawrence Carin, David M. Blei, Ingrid Daubechies:
A Bayesian Nonparametric Approach to Image Super-resolution. CoRR abs/1209.5019 (2012) - [i3]Lingbo Li, XianXing Zhang, Mingyuan Zhou, Lawrence Carin:
Nested Dictionary Learning for Hierarchical Organization of Imagery and Text. CoRR abs/1210.4872 (2012) - 2011
- [j83]Lu Ren, Lan Du, Lawrence Carin, David B. Dunson:
Logistic Stick-Breaking Process. J. Mach. Learn. Res. 12: 203-239 (2011) - [j82]Lawrence Carin, Richard G. Baraniuk, Volkan Cevher, David B. Dunson, Michael I. Jordan, Guillermo Sapiro, Michael B. Wakin:
Learning Low-Dimensional Signal Models. IEEE Signal Process. Mag. 28(2): 39-51 (2011) - [j81]Minhua Chen, David E. Carlson, Aimee K. Zaas, Christopher W. Woods, Geoffrey S. Ginsburg, Alfred O. Hero III, Joseph E. Lucas, Lawrence Carin:
Detection of Viruses Via Statistical Gene Expression Analysis. IEEE Trans. Biomed. Eng. 58(3): 468-479 (2011) - [j80]Alexey Castrodad, Zhengming Xing, John B. Greer, Edward Bosch, Lawrence Carin, Guillermo Sapiro:
Learning Discriminative Sparse Representations for Modeling, Source Separation, and Mapping of Hyperspectral Imagery. IEEE Trans. Geosci. Remote. Sens. 49(11): 4263-4281 (2011) - [j79]Xinghao Ding, Lihan He, Lawrence Carin:
Bayesian Robust Principal Component Analysis. IEEE Trans. Image Process. 20(12): 3419-3430 (2011) - [j78]Minhua Chen, Jorge G. Silva, John W. Paisley, Chunping Wang, David B. Dunson, Lawrence Carin:
Corrections to "Compressive Sensing on Manifolds Using a Nonparametric Mixture of Factor Analyzers: Algorithm and Performance Bounds". IEEE Trans. Signal Process. 59(3): 1329 (2011) - [c80]Priyadip Ray, Lawrence Carin:
Non-parametric Bayesian modeling and fusion of spatio-temporal information sources. FUSION 2011: 1-7 - [c79]Christopher Cramer, Lawrence Carin:
Bayesian topic models for describing computer network behaviors. ICASSP 2011: 1888-1891 - [c78]Lingbo Li, Mingyuan Zhou, Eric Wang, Lawrence Carin:
Joint dictionary learning and topic modeling for image clustering. ICASSP 2011: 2168-2171 - [c77]Eric Wang, Jorge G. Silva, Rebecca Willett, Lawrence Carin:
Time-evolving modeling of social networks. ICASSP 2011: 2184-2187 - [c76]Hui Li, Xuejun Liao, Lawrence Carin:
Nonparametric Bayesian feature selection for multi-task learning. ICASSP 2011: 2236-2239 - [c75]Mingyuan Zhou, Hongxia Yang, Guillermo Sapiro, David B. Dunson, Lawrence Carin:
Covariate-dependent dictionary learning and sparse coding. ICASSP 2011: 5824-5827 - [c74]Bo Chen, Gungor Polatkan, Guillermo Sapiro, David B. Dunson, Lawrence Carin:
The Hierarchical Beta Process for Convolutional Factor Analysis and Deep Learning. ICML 2011: 361-368 - [c73]Haojun Chen, David B. Dunson, Lawrence Carin:
Topic Modeling with Nonparametric Markov Tree. ICML 2011: 377-384 - [c72]Lingbo Li, Mingyuan Zhou, Guillermo Sapiro, Lawrence Carin:
On the Integration of Topic Modeling and Dictionary Learning. ICML 2011: 625-632 - [c71]Miao Liu, Xuejun Liao, Lawrence Carin:
The Infinite Regionalized Policy Representation. ICML 2011: 769-776 - [c70]XianXing Zhang, David B. Dunson, Lawrence Carin:
Tree-Structured Infinite Sparse Factor Model. ICML 2011: 785-792 - [c69]John W. Paisley, Lawrence Carin, David M. Blei:
Variational Inference for Stick-Breaking Beta Process Priors. ICML 2011: 889-896 - [c68]Bo Chen, David E. Carlson, Lawrence Carin:
On the Analysis of Multi-Channel Neural Spike Data. NIPS 2011: 936-944 - [c67]Lu Ren, Yingjian Wang, David B. Dunson, Lawrence Carin:
The Kernel Beta Process. NIPS 2011: 963-971 - [c66]XianXing Zhang, David B. Dunson, Lawrence Carin:
Hierarchical Topic Modeling for Analysis of Time-Evolving Personal Choices. NIPS 2011: 1395-1403 - [c65]Mingyuan Zhou, Hongxia Yang, Guillermo Sapiro, David B. Dunson, Lawrence Carin:
Dependent Hierarchical Beta Process for Image Interpolation and Denoising. AISTATS 2011: 883-891 - [i2]Jorge G. Silva, Minhua Chen, Yonina C. Eldar, Guillermo Sapiro, Lawrence Carin:
Blind Compressed Sensing Over a Structured Union of Subspaces. CoRR abs/1103.2469 (2011) - [i1]Julio Martin Duarte-Carvajalino, Guillermo Sapiro, Guoshen Yu, Lawrence Carin:
Online Adaptive Statistical Compressed Sensing of Gaussian Mixture Models. CoRR abs/1112.5895 (2011) - 2010
- [j77]Bo Chen, Minhua Chen, John W. Paisley, Aimee K. Zaas, Christopher W. Woods, Geoffrey S. Ginsburg, Alfred O. Hero III, Joseph E. Lucas, David B. Dunson, Lawrence Carin:
Bayesian Inference of the Number of Factors in Gene-Expression Analysis: Application to Human Virus Challenge Studies. BMC Bioinform. 11: 552 (2010) - [j76]Chunping Wang, Xuejun Liao, Lawrence Carin, David B. Dunson:
Classification with Incomplete Data Using Dirichlet Process Priors. J. Mach. Learn. Res. 11: 3269-3311 (2010) - [j75]Iulian Pruteanu-Malinici, Lu Ren, John W. Paisley, Eric Wang, Lawrence Carin:
Hierarchical Bayesian Modeling of Topics in Time-Stamped Documents. IEEE Trans. Pattern Anal. Mach. Intell. 32(6): 996-1011 (2010) - [j74]Lihan He, Haojun Chen, Lawrence Carin:
Tree-Structured Compressive Sensing With Variational Bayesian Analysis. IEEE Signal Process. Lett. 17(3): 233-236 (2010) - [j73]David M. Blei, Lawrence Carin, David B. Dunson:
Probabilistic Topic Models. IEEE Signal Process. Mag. 27(6): 55-65 (2010) - [j72]Volkan Cevher, Piotr Indyk, Lawrence Carin, Richard G. Baraniuk:
Sparse Signal Recovery and Acquisition with Graphical Models. IEEE Signal Process. Mag. 27(6): 92-103 (2010) - [j71]John W. Paisley, Xuejun Liao, Lawrence Carin:
Active learning and basis selection for kernel-based linear models: a Bayesian perspective. IEEE Trans. Signal Process. 58(5): 2686-2700 (2010) - [j70]Lan Du, Minhua Chen, Joseph E. Lucas, Lawrence Carin:
Sticky hidden Markov modeling of comparative genomic hybridization. IEEE Trans. Signal Process. 58(10): 5353-5368 (2010) - [j69]Minhua Chen, Jorge G. Silva, John W. Paisley, Chunping Wang, David B. Dunson, Lawrence Carin:
Compressive Sensing on Manifolds Using a Nonparametric Mixture of Factor Analyzers: Algorithm and Performance Bounds. IEEE Trans. Signal Process. 58(12): 6140-6155 (2010) - [c64]Yi Ma, Fei Sha, Lawrence Carin, Gilad Lerman, Neil D. Lawrence:
Invited Talk Abstracts. AAAI Fall Symposium: Manifold Learning and Its Applications 2010 - [c63]Bo Chen, John W. Paisley, Lawrence Carin:
Sparse linear regression with beta process priors. ICASSP 2010: 1234-1237 - [c62]John W. Paisley, Lawrence Carin:
A nonparametric Bayesian model for kernel matrix completion. ICASSP 2010: 2090-2093 - [c61]Alexey Castrodad, Zhengming Xing, John B. Greer, Edward Bosch, Lawrence Carin, Guillermo Sapiro:
Discriminative sparse representations in hyperspectral imagery. ICIP 2010: 1313-1316 - [c60]John W. Paisley, Mingyuan Zhou, Guillermo Sapiro, Lawrence Carin:
Nonparametric image interpolation and dictionary learning using spatially-dependent Dirichlet and beta process priors. ICIP 2010: 1869-1872 - [c59]John W. Paisley, Aimee K. Zaas, Christopher W. Woods, Geoffrey S. Ginsburg, Lawrence Carin:
A Stick-Breaking Construction of the Beta Process. ICML 2010: 847-854 - [c58]Eric Wang, Dehong Liu, Jorge G. Silva, David B. Dunson, Lawrence Carin:
Joint Analysis of Time-Evolving Binary Matrices and Associated Documents. NIPS 2010: 2370-2378
2000 – 2009
- 2009
- [j68]Lawrence Carin, Dehong Liu, Wenbin Lin, Bin Guo:
Compressive sensing for multi-static scattering analysis. J. Comput. Phys. 228(9): 3464-3477 (2009) - [j67]Hui Li, Xuejun Liao, Lawrence Carin:
Multi-task Reinforcement Learning in Partially Observable Stochastic Environments. J. Mach. Learn. Res. 10: 1131-1186 (2009) - [j66]Shihao Ji, Layne T. Watson, Lawrence Carin:
Semisupervised Learning of Hidden Markov Models via a Homotopy Method. IEEE Trans. Pattern Anal. Mach. Intell. 31(2): 275-287 (2009) - [j65]Qiuhua Liu, Xuejun Liao, Hui Li, Jason R. Stack, Lawrence Carin:
Semisupervised Multitask Learning. IEEE Trans. Pattern Anal. Mach. Intell. 31(6): 1074-1086 (2009) - [j64]Xuejun Liao, Lawrence Carin:
Migratory Logistic Regression for Learning Concept Drift Between Two Data Sets With Application to UXO Sensing. IEEE Trans. Geosci. Remote. Sens. 47(5): 1454-1466 (2009) - [j63]Jason R. Stack, Gerald J. Dobeck, Xuejun Liao, Lawrence Carin:
Kernel-Matching Pursuits With Arbitrary Loss Functions. IEEE Trans. Neural Networks 20(3): 395-405 (2009) - [j62]Shihao Ji, David B. Dunson, Lawrence Carin:
Multitask Compressive Sensing. IEEE Trans. Signal Process. 57(1): 92-106 (2009) - [j61]Lihan He, Lawrence Carin:
Exploiting structure in wavelet-based Bayesian compressive sensing. IEEE Trans. Signal Process. 57(9): 3488-3497 (2009) - [j60]John W. Paisley, Lawrence Carin:
Hidden Markov models with stick-breaking priors. IEEE Trans. Signal Process. 57(10): 3905-3917 (2009) - [c57]Chunping Wang, Qi An, Lawrence Carin, David B. Dunson:
Multi-task classification with infinite local experts. ICASSP 2009: 1569-1572 - [c56]John W. Paisley, Lawrence Carin:
Dirichlet process mixture models with multiple modalities. ICASSP 2009: 1613-1616 - [c55]Hui Li, Xuejun Liao, Lawrence Carin:
Active learning for semi-supervised multi-task learning. ICASSP 2009: 1637-1640 - [c54]Lu Ren, David B. Dunson, Scott Lindroth, Lawrence Carin:
Music analysis with a Bayesian dynamic model. ICASSP 2009: 1681-1684 - [c53]John W. Paisley, Lawrence Carin:
Nonparametric factor analysis with beta process priors. ICML 2009: 777-784 - [c52]Chenghui Cai, Xuejun Liao, Lawrence Carin:
Learning to Explore and Exploit in POMDPs. NIPS 2009: 198-206 - [c51]Lan Du, Lu Ren, David B. Dunson, Lawrence Carin:
A Bayesian Model for Simultaneous Image Clustering, Annotation and Object Segmentation. NIPS 2009: 486-494 - [c50]Mingyuan Zhou, Haojun Chen, John W. Paisley, Lu Ren, Guillermo Sapiro, Lawrence Carin:
Non-Parametric Bayesian Dictionary Learning for Sparse Image Representations. NIPS 2009: 2295-2303 - 2008
- [j59]Lawrence Carin, George Cybenko, Jeff Hughes:
Cybersecurity Strategies: The QuERIES Methodology. Computer 41(8): 20-26 (2008) - [j58]Jun Fang, Shihao Ji, Ya Xue, Lawrence Carin:
Multitask Classification by Learning the Task Relevance. IEEE Signal Process. Lett. 15: 593-596 (2008) - [j57]K. C. Ho, Lawrence Carin, Paul D. Gader, Joseph N. Wilson:
An Investigation of Using the Spectral Characteristics From Ground Penetrating Radar for Landmine/Clutter Discrimination. IEEE Trans. Geosci. Remote. Sens. 46(4): 1177-1191 (2008) - [j56]Qiuhua Liu, Xuejun Liao, Lawrence Carin:
Detection of Unexploded Ordnance via Efficient Semisupervised and Active Learning. IEEE Trans. Geosci. Remote. Sens. 46(9): 2558-2567 (2008) - [j55]Iulian Pruteanu-Malinici, Lawrence Carin:
Infinite Hidden Markov Models for Unusual-Event Detection in Video. IEEE Trans. Image Process. 17(5): 811-822 (2008) - [j54]Shihao Ji, Ya Xue, Lawrence Carin:
Bayesian Compressive Sensing. IEEE Trans. Signal Process. 56(6): 2346-2356 (2008) - [j53]Kai Ni, John W. Paisley, Lawrence Carin, David B. Dunson:
Multi-Task Learning for Analyzing and Sorting Large Databases of Sequential Data. IEEE Trans. Signal Process. 56(8-2): 3918-3931 (2008) - [c49]Qi An, Chunping Wang, Ivo Shterev, Eric Wang, Lawrence Carin, David B. Dunson:
Hierarchical kernel stick-breaking process for multi-task image analysis. ICML 2008: 17-24 - [c48]Yuting Qi, Dehong Liu, David B. Dunson, Lawrence Carin:
Multi-task compressive sensing with Dirichlet process priors. ICML 2008: 768-775 - [c47]Lu Ren, David B. Dunson, Lawrence Carin:
The dynamic hierarchical Dirichlet process. ICML 2008: 824-831 - [c46]Gregory Arnold, Timothy Ross, Lori Westerkamp, Lawrence Carin, Randolph L. Moses:
The ATR Center and ATRpedia. Visual Information Processing 2008: 69780 - 2007
- [j52]Zhiqin Zhao, Narayan Kovvali, Wenbin Lin, Chang-Hoi Ahn, Luise Couchman, Lawrence Carin:
Volumetric fast multipole method for modeling Schrödinger's equation. J. Comput. Phys. 224(2): 941-955 (2007) - [j51]Ya Xue, Xuejun Liao, Lawrence Carin, Balaji Krishnapuram:
Multi-Task Learning for Classification with Dirichlet Process Priors. J. Mach. Learn. Res. 8: 35-63 (2007) - [j50]David Williams, Yijun Yu, Levi Kennedy, Xianyang Zhu, Lawrence Carin:
A Bivariate Gaussian Model for Unexploded Ordnance Classification with EMI Data. IEEE Geosci. Remote. Sens. Lett. 4(4): 629-633 (2007) - [j49]David Williams, Xuejun Liao, Ya Xue, Lawrence Carin, Balaji Krishnapuram:
On Classification with Incomplete Data. IEEE Trans. Pattern Anal. Mach. Intell. 29(3): 427-436 (2007) - [j48]Shihao Ji, Lawrence Carin:
Cost-sensitive feature acquisition and classification. Pattern Recognit. 40(5): 1474-1485 (2007) - [j47]Dehong Liu, Jeffrey L. Krolik, Lawrence Carin:
Electromagnetic Target Detection in Uncertain Media: Time-Reversal and Minimum-Variance Algorithms. IEEE Trans. Geosci. Remote. Sens. 45(4): 934-944 (2007) - [j46]Yijun Yu, Lawrence Carin:
Three-Dimensional Bayesian Inversion With Application to Subsurface Sensing. IEEE Trans. Geosci. Remote. Sens. 45(5-1): 1258-1270 (2007) - [j45]Lihan He, Shihao Ji, Waymond R. Scott, Lawrence Carin:
Adaptive Multimodality Sensing of Landmines. IEEE Trans. Geosci. Remote. Sens. 45(6-2): 1756-1774 (2007) - [j44]David Williams, Chunping Wang, Xuejun Liao, Lawrence Carin:
Classification of Unexploded Ordnance Using Incomplete Multisensor Multiresolution Data. IEEE Trans. Geosci. Remote. Sens. 45(7-2): 2364-2373 (2007) - [j43]Shihao Ji, Ronald Parr, Lawrence Carin:
Nonmyopic Multiaspect Sensing With Partially Observable Markov Decision Processes. IEEE Trans. Signal Process. 55(6-1): 2720-2730 (2007) - [j42]Yuting Qi, John William Paisley, Lawrence Carin:
Music Analysis Using Hidden Markov Mixture Models. IEEE Trans. Signal Process. 55(11): 5209-5224 (2007) - [c45]Shihao Ji, Ronald Parr, Hui Li, Xuejun Liao, Lawrence Carin:
Point-Based Policy Iteration. AAAI 2007: 1243-1249 - [c44]Kai Ni, Yuting Qi, Lawrence Carin:
Multi-Aspect Target Classification and Detection via the Infinite Hidden Markov Model. ICASSP (2) 2007: 433-436 - [c43]Yuting Qi, John William Paisley, Lawrence Carin:
Dirichlet Process HMM Mixture Models with Application to Music Analysis. ICASSP (2) 2007: 465-468 - [c42]Dehong Liu, Lawrence Carin:
Wideband Array Imaging of a Target Situated in an Unknown Random Media. ICASSP (1) 2007: 533-536 - [c41]Qiuhua Liu, Xuejun Liao, Lawrence Carin:
Learning Classifiers on a Partially Labeled Data Manifold. ICASSP (2) 2007: 621-624 - [c40]Iulian Pruteanu-Malinici, Lawrence Carin:
Infinite Hidden Markov Models and ISA Features for Unusual-Event Detection in Video. ICIP (5) 2007: 137-140 - [c39]Shihao Ji, Lawrence Carin:
Bayesian compressive sensing and projection optimization. ICML 2007: 377-384 - [c38]Xuejun Liao, Hui Li, Lawrence Carin:
Quadratically gated mixture of experts for incomplete data classification. ICML 2007: 553-560 - [c37]Kai Ni, Lawrence Carin, David B. Dunson:
Multi-task learning for sequential data via iHMMs and the nested Dirichlet process. ICML 2007: 689-696 - [c36]Ya Xue, David B. Dunson, Lawrence Carin:
The matrix stick-breaking process for flexible multi-task learning. ICML 2007: 1063-1070 - [c35]Qiuhua Liu, Xuejun Liao, Lawrence Carin:
Semi-Supervised Multitask Learning. NIPS 2007: 937-944 - 2006
- [j41]Wenbin Lin, Narayan Kovvali, Lawrence Carin:
Pseudospectral method based on prolate spheroidal wave functions for semiconductor nanodevice simulation. Comput. Phys. Commun. 175(2): 78-85 (2006) - [j40]Shihao Ji, Balaji Krishnapuram, Lawrence Carin:
Variational Bayes for Continuous Hidden Markov Models and Its Application to Active Learning. IEEE Trans. Pattern Anal. Mach. Intell. 28(4): 522-532 (2006) - [j39]Narayan Kovvali, Wenbin Lin, Zhiqin Zhao, Luise Couchman, Lawrence Carin:
Rapid Prolate Pseudospectral Differentiation and Interpolation with the Fast Multipole Method. SIAM J. Sci. Comput. 28(2): 485-497 (2006) - [j38]Shaorong Chang, Lawrence Carin:
A modified SPIHT algorithm for image coding with a joint MSE and classification distortion measure. IEEE Trans. Image Process. 15(3): 713-725 (2006) - [j37]Nilanjan Dasgupta, Lawrence Carin:
Texture analysis with variational hidden Markov trees. IEEE Trans. Signal Process. 54(6-1): 2353-2356 (2006) - [c34]Hui Li, Xuejun Liao, Lawrence Carin:
Incremental Least Squares Policy Iteration for POMDPs. AAAI 2006: 1167-1172 - [c33]Nilanjan Dasgupta, Shihao Ji, Lawrence Carin:
Homotopy-Based Semi-Supervised Hidden Markov Tree for Texture Analysis. ICASSP (2) 2006: 97-100 - [c32]Hui Li, Xuejun Liao, Lawrence Carin:
A Reward-Directed Bayesian Classifier. ICASSP (5) 2006: 613-616 - [c31]Hui Li, Xuejun Liao, Lawrence Carin:
Region-based value iteration for partially observable Markov decision processes. ICML 2006: 561-568 - 2005
- [j36]Wenbin Lin, Narayan Kovvali, Lawrence Carin:
Direct algorithm for computation of derivatives of the Daubechies basis functions. Appl. Math. Comput. 170(2): 1006-1013 (2005) - [j35]Balaji Krishnapuram, Lawrence Carin, Mário A. T. Figueiredo, Alexander J. Hartemink:
Sparse Multinomial Logistic Regression: Fast Algorithms and Generalization Bounds. IEEE Trans. Pattern Anal. Mach. Intell. 27(6): 957-968 (2005) - [c30]Shaorong Chang, Nilanjan Dasgupta, Lawrence Carin:
A Bayesian Approach to Unsupervised Feature Selection and Density Estimation Using Expectation Propagation. CVPR (2) 2005: 1043-1050 - [c29]Xuejun Liao, Ya Xue, Lawrence Carin:
Logistic regression with an auxiliary data source. ICML 2005: 505-512 - [c28]David Williams, Xuejun Liao, Ya Xue, Lawrence Carin:
Incomplete-data classification using logistic regression. ICML 2005: 972-979 - [c27]Xuejun Liao, Lawrence Carin:
Radial Basis Function Network for Multi-task Learning. NIPS 2005: 792-802 - 2004
- [j34]Balaji Krishnapuram, Lawrence Carin, Alexander J. Hartemink:
Joint Classifier and Feature Optimization for Comprehensive Cancer Diagnosis Using Gene Expression Data. J. Comput. Biol. 11(2/3): 227-242 (2004) - [j33]Xuejun Liao, Lawrence Carin:
Application of the Theory of Optimal Experiments to Adaptive Electromagnetic-Induction Sensing of Buried Targets. IEEE Trans. Pattern Anal. Mach. Intell. 26(8): 961-972 (2004) - [j32]Balaji Krishnapuram, Alexander J. Hartemink, Lawrence Carin, Mário A. T. Figueiredo:
A Bayesian Approach to Joint Feature Selection and Classifier Design. IEEE Trans. Pattern Anal. Mach. Intell. 26(9): 1105-1111 (2004) - [j31]Yijun Yu, Tiejun Yu, Lawrence Carin:
Three-dimensional inverse scattering of a dielectric target embedded in a lossy half-space. IEEE Trans. Geosci. Remote. Sens. 42(5): 957-973 (2004) - [j30]Xianyang Zhu, Lawrence Carin:
Application of the biorthogonal multiresolution time-domain method to the analysis of elastic-wave interactions with buried targets. IEEE Trans. Geosci. Remote. Sens. 42(7): 1502-1511 (2004) - [j29]Yan Zhang, Xuejun Liao, Lawrence Carin:
Detection of buried targets via active selection of labeled data: application to sensing subsurface UXO. IEEE Trans. Geosci. Remote. Sens. 42(11): 2535-2543 (2004) - [c26]Nilanjan Dasgupta, Lawrence Carin:
Time-reversal imaging and classification for distant targets in a shallow water channel. ICASSP (2) 2004: 65-68 - [c25]Shihao Ji, Xuejun Liao, Lawrence Carin:
Adaptive multi-aspect target classification and detection with hidden Markov models. ICASSP (2) 2004: 125-128 - [c24]Yan Zhang, Xuejun Liao, Esther Durá, Lawrence Carin:
Active selection of labeled data for target detection. ICASSP (5) 2004: 465-468 - [c23]Shaorong Chang, Lawrence Carin:
Kernel matching pursuits prioritization of wavelet coefficients for SPIHT image coding. ICASSP (3) 2004: 649-652 - [c22]Dehong Liu, Lihan He, Lawrence Carin:
Airport detection in large aerial optical imagery. ICASSP (5) 2004: 761-764 - [c21]Balaji Krishnapuram, David Williams, Ya Xue, Alexander J. Hartemink, Lawrence Carin, Mário A. T. Figueiredo:
On Semi-Supervised Classification. NIPS 2004: 721-728 - 2003
- [j28]Yan Zhang, Leslie M. Collins, Lawrence Carin:
Unexploded ordnance detection using Bayesian physics-based data fusion. Integr. Comput. Aided Eng. 10(3): 231-247 (2003) - [j27]Yanting Dong, Lawrence Carin:
Rate-Distortion Analysis of Discrete-HMM Pose Estimation via Multiaspect Scattering Data. IEEE Trans. Pattern Anal. Mach. Intell. 25(7): 872-883 (2003) - [j26]Ling Li, Zhijun Liu, Xiaolong Dong, James A. Thompson, Lawrence Carin:
Scalable multilevel fast multipole method for multiple targets in the vicinity of a half space. IEEE Trans. Geosci. Remote. Sens. 41(4): 791-802 (2003) - [j25]Yan Zhang, Leslie M. Collins, Haitao Yu, Carl E. Baum, Lawrence Carin:
Sensing of unexploded ordnance with magnetometer and induction data: theory and signal processing. IEEE Trans. Geosci. Remote. Sens. 41(5): 1005-1015 (2003) - [j24]Yanting Dong, Lawrence Carin:
Quantization of multiaspect scattering data: target classification and pose estimation. IEEE Trans. Signal Process. 51(12): 3105-3114 (2003) - [c20]Yanting Dong, Lawrence Carin:
Rate-Distortion Bound for Joint Compression and Classification. DCC 2003: 423 - [c19]Hongwei Liu, Nilanjan Dasgupta, Lawrence Carin:
Time-reversal imaging for wideband underwater target classification. ICASSP (5) 2003: 5-8 - [c18]Xuejun Liao, Lawrence Carin:
ICA with multiple quadratic constraints. ICASSP (5) 2003: 313-316 - [c17]Nilanjan Dasgupta, Lawrence Carin:
Context-based graphical modeling for wavelet domain signal processing. ICASSP (3) 2003: 485-488 - [c16]Balaji Krishnapuram, Lawrence Carin, Alexander J. Hartemink:
Joint classifier and feature optimization for cancer diagnosis using gene expression data. RECOMB 2003: 167-175 - 2002
- [j23]Priya Bharadwaj, Lawrence Carin:
Infrared-Image Classification Using Hidden Markov Trees. IEEE Trans. Pattern Anal. Mach. Intell. 24(10): 1394-1398 (2002) - [j22]Nilanjan Dasgupta, Simon M. Lin, Lawrence Carin:
Sequential modeling for identifying CpG island locations in human genome. IEEE Signal Process. Lett. 9(12): 407-409 (2002) - [c15]Hongwei Liu, Lawrence Carin:
Class-based target classification in shallow water channel based on Hidden Markov Model. ICASSP 2002: 2889-2892 - [c14]Balaji Krishnapuram, Lawrence Carin:
Support Vector Machines for improved multiaspect target recognition using the fisher kernel scores of Hidden Markov Models. ICASSP 2002: 2989-2992 - [c13]Jiuliu Lu, Lawrence Carin:
HMM-based multiresolution image segmentation. ICASSP 2002: 3357-3360 - [c12]Xuejun Liao, Nilanjan Dasgupta, Simon M. Lin, Lawrence Carin:
ICA and PLS modeling for functional analysis and drug sensitivity for DNA microarray signals. ICASSP 2002: 3880-3883 - [c11]Shaorong Chang, Nasser M. Nasrabadi, Lawrence Carin:
Infrared-image classification using support vector machines. ICASSP 2002: 4168 - [c10]Leslie M. Collins, Yizhe Zhang, Lawrence Carin:
Model-based statistical sensor fusion for unexploded ordnance detection. IGARSS 2002: 1556-1559 - [c9]Balaji Krishnapuram, Lawrence Carin:
Support Vector Machines for Improved Multiaspect Target Recognition Using the Fisher Scores of Hidden Markov Models. JCIS 2002: 354-357 - 2001
- [j21]Eric Jones, Paul Runkle, Nilanjan Dasgupta, Luise Couchman, Lawrence Carin:
Genetic Algorithm Wavelet Design for Signal Classification. IEEE Trans. Pattern Anal. Mach. Intell. 23(8): 890-895 (2001) - [j20]Nilanjan Dasgupta, Paul Runkle, Luise Couchman, Lawrence Carin:
Dual hidden Markov model for characterizing wavelet coefficients from multi-aspect scattering data. Signal Process. 81(6): 1303-1316 (2001) - [j19]Leslie M. Collins, Yan Zhang, Jing Li, Hua Wang, Lawrence Carin, Sean J. Hart, Susan L. Rose-Pehrsson, Herbert H. Nelson, James R. McDonald:
A comparison of the performance of statistical and fuzzy algorithms for unexploded ordnance detection. IEEE Trans. Fuzzy Syst. 9(1): 17-30 (2001) - [j18]Paul Runkle, Lam H. Nguyen, James H. McClellan, Lawrence Carin:
Multi-aspect target detection for SAR imagery using hidden Markov models. IEEE Trans. Geosci. Remote. Sens. 39(1): 46-55 (2001) - [j17]Lawrence Carin:
Foreword. IEEE Trans. Geosci. Remote. Sens. 39(6): 1107 (2001) - [j16]Lawrence Carin, Haitao Yu, Yacine Dalichaouch, Alexander R. Perry, Peter V. Czipott, Carl E. Baum:
On the wideband EMI response of a rotationally symmetric permeable and conducting target. IEEE Trans. Geosci. Remote. Sens. 39(6): 1206-1213 (2001) - [j15]Yanting Dong, Paul Runkle, Lawrence Carin, Raju Damarla, Anders Sullivan, Marc A. Ressler, Jeffrey Sichina:
Multi-aspect detection of surface and shallow-buried unexploded ordnance via ultra-wideband synthetic aperture radar. IEEE Trans. Geosci. Remote. Sens. 39(6): 1259-1270 (2001) - [j14]Traian Dogaru, Lawrence Carin:
Time-domain sensing of targets buried under a Gaussian, exponential, or fractal rough interface. IEEE Trans. Geosci. Remote. Sens. 39(8): 1807-1819 (2001) - [j13]Jiangqi He, Norbert Geng, Lam H. Nguyen, Lawrence Carin:
Rigorous modeling of ultrawideband VHF scattering from tree trunks over flat and. sloped terrain. IEEE Trans. Geosci. Remote. Sens. 39(10): 2182-2193 (2001) - [c8]Priya Bharadwaj, Paul Runkle, Lawrence Carin:
Infrared-image classification using expansion matching filters and hidden Markov trees. ICASSP 2001: 1553-1556 - [c7]Yanting Dong, Paul Runkle, Lawrence Carin:
Markov modeling of transient scattering and its application in multi-aspect target classification. ICASSP 2001: 2841-2844 - [c6]Xuejun Liao, Paul Runkle, Yan Jiao, Lawrence Carin:
Identification of ground targets from sequential HRR radar signatures. ICASSP 2001: 2897-2900 - [c5]Nilanjan Dasgupta, Paul Runkle, Lawrence Carin:
Class-based identification of underwater targets using hidden Markov models. ICASSP 2001: 3161-3164 - 2000
- [j12]Tiejun Yu, Lawrence Carin:
Analysis of the electromagnetic inductive response of a void in a conducting-soil background. IEEE Trans. Geosci. Remote. Sens. 38(3): 1320-1327 (2000) - [j11]Ping Gao, Leslie M. Collins, Philip M. Garber, Norbert Geng, Lawrence Carin:
Classification of landmine-like metal targets using wideband electromagnetic induction. IEEE Trans. Geosci. Remote. Sens. 38(3): 1352-1361 (2000) - [j10]Norbert Geng, Anders Sullivan, Lawrence Carin:
Multilevel fast-multipole algorithm for scattering from conducting targets above or embedded in a lossy half space. IEEE Trans. Geosci. Remote. Sens. 38(4): 1561-1573 (2000)
1990 – 1999
- 1999
- [j9]Paul Runkle, Lawrence Carin, Luise Couchman, Timothy J. Yoder, Joseph A. Bucaro:
Multiaspect Target Identification with Wave-Based Matched Pursuits and Continuous Hidden Markov Models. IEEE Trans. Pattern Anal. Mach. Intell. 21(12): 1371-1378 (1999) - [j8]Norbert Geng, Carl E. Baum, Lawrence Carin:
On the low-frequency natural response of conducting and permeable targets. IEEE Trans. Geosci. Remote. Sens. 37(1): 347-359 (1999) - [j7]Leslie M. Collins, Ping Gao, Lawrence Carin:
An improved Bayesian decision theoretic approach for land mine detection. IEEE Trans. Geosci. Remote. Sens. 37(2): 811-819 (1999) - [j6]Norbert Geng, Lawrence Carin:
Short-pulse electromagnetic scattering from arbitrarily oriented subsurface ordnance. IEEE Trans. Geosci. Remote. Sens. 37(4): 2111-2113 (1999) - [j5]Norbert Geng, Marc A. Ressler, Lawrence Carin:
Wide-band VHF scattering from a trihedral reflector situated above a lossy dispersive halfspace. IEEE Trans. Geosci. Remote. Sens. 37(5): 2609-2617 (1999) - [j4]Luise Couchman, Lawrence Carin:
Hidden Markov models for multiaspect target classification. IEEE Trans. Signal Process. 47(7): 2035-2040 (1999) - [c4]Paul Runkle, Lawrence Carin:
Multi-aspect target identification with wave-based matching pursuits and continuous hidden Markov models. ICASSP 1999: 2115-2118 - [c3]Ping Gao, Leslie M. Collins, Norbert Geng, Lawrence Carin, Dean A. Keiswetter, I. J. Won:
Classification of landmine-like metal targets using wideband electromagnetic induction. ICASSP 1999: 2327-2330 - [c2]Lawrence Carin, Gary Ybarra, Priya Bharadwaj, Paul Runkle:
Physics-based classification of targets in SAR imagery using subaperture sequences. ICASSP 1999: 3341-3344 - 1998
- [j3]Lawrence Carin, Ravinder Kapoor, Carl E. Baum:
Polarimetric SAR imaging of buried landmines. IEEE Trans. Geosci. Remote. Sens. 36(6): 1985-1988 (1998) - 1997
- [j2]Stanislav Vitebskiy, Lawrence Carin, Marc A. Ressler, Francis H. Le:
Ultra-wideband, short-pulse ground-penetrating radar: simulation and measurement. IEEE Trans. Geosci. Remote. Sens. 35(3): 762-772 (1997) - [j1]Mark R. McClure, Lawrence Carin:
Matching pursuits with a wave-based dictionary. IEEE Trans. Signal Process. 45(12): 2912-2927 (1997) - [c1]Hakan Bakircioglu, Erol Gelenbe, Lawrence Carin:
Random Neural Network Recognition of Shaped Objects in Strong Clutter. ICANN 1997: 961-966
Coauthor Index
David E. Carlson
aka: David Edwin Carlson
aka: David Edwin Carlson
[c291] [c286] [i157] [c272] [c270] [c269] [c261] [i149] [i136] [i135] [i115] [j114] [c243] [c238] [c237] [c236] [c233] [c226] [c220] [i108] [i105] [i103] [i102] [i97] [c218] [c209] [c208] [c202] [c197] [i73] [i63] [i60] [i57] [c188] [c186] [c179] [c168] [i51] [i48] [i39] [i38] [c165] [c164] [c160] [c155] [c151] [c149] [c147] [c145] [c144] [i32] [i31] [i26] [c137] [c129] [c124] [i20] [i17]