Stop the war!Остановите войну!
for scientists:
default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDLawrence Carin
Person information
- affiliation: Duke University, Durham, USA
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2023
[j123]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)- [j122]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) - [j121]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) - [c306]Vinay Kumar Verma, Nikhil Mehta, Shijing Si, Ricardo Henao, Lawrence Carin:
Pushing the Efficiency Limit Using Structured Sparse Convolutions. WACV 2023: 6492-6502 - [i173]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) - 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]