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2020 – today
- 2023
- [j7]Jinsung Yoon, Kihyuk Sohn, Chun-Liang Li, Sercan Ö. Arik, Tomas Pfister:
SPADE: Semi-supervised Anomaly Detection under Distribution Mismatch. Trans. Mach. Learn. Res. 2023 (2023) - [c40]Kihyuk Sohn, Jinsung Yoon, Chun-Liang Li, Chen-Yu Lee, Tomas Pfister:
Anomaly Clustering: Grouping Images into Coherent Clusters of Anomaly Types. WACV 2023: 5468-5479 - [c39]Justin Lazarow, Kihyuk Sohn, Chen-Yu Lee, Chun-Liang Li, Zizhao Zhang, Tomas Pfister:
Unifying Distribution Alignment as a Loss for Imbalanced Semi-supervised Learning. WACV 2023: 5633-5642 - [i47]Ruoxi Sun, Chun-Liang Li, Sercan Ö. Arik, Michael W. Dusenberry, Chen-Yu Lee, Tomas Pfister:
Neural Spline Search for Quantile Probabilistic Modeling. CoRR abs/2301.04857 (2023) - [i46]Kuniaki Saito, Kihyuk Sohn, Xiang Zhang, Chun-Liang Li, Chen-Yu Lee, Kate Saenko, Tomas Pfister:
Pic2Word: Mapping Pictures to Words for Zero-shot Composed Image Retrieval. CoRR abs/2302.03084 (2023) - [i45]Si-An Chen, Chun-Liang Li, Nate Yoder, Sercan Ö. Arik, Tomas Pfister:
TSMixer: An all-MLP Architecture for Time Series Forecasting. CoRR abs/2303.06053 (2023) - [i44]Cheng-Yu Hsieh, Chun-Liang Li, Chih-Kuan Yeh, Hootan Nakhost, Yasuhisa Fujii, Alexander Ratner, Ranjay Krishna, Chen-Yu Lee, Tomas Pfister:
Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes. CoRR abs/2305.02301 (2023) - [i43]Chen-Yu Lee, Chun-Liang Li, Hao Zhang, Timothy Dozat, Vincent Perot, Guolong Su, Xiang Zhang, Kihyuk Sohn, Nikolai Glushnev, Renshen Wang, Joshua Ainslie, Shangbang Long, Siyang Qin, Yasuhisa Fujii, Nan Hua, Tomas Pfister:
FormNetV2: Multimodal Graph Contrastive Learning for Form Document Information Extraction. CoRR abs/2305.02549 (2023) - 2022
- [j6]Jinsung Yoon, Kihyuk Sohn, Chun-Liang Li, Sercan Ö. Arik, Chen-Yu Lee, Tomas Pfister:
Self-supervise, Refine, Repeat: Improving Unsupervised Anomaly Detection. Trans. Mach. Learn. Res. 2022 (2022) - [c38]Chen-Yu Lee, Chun-Liang Li, Timothy Dozat, Vincent Perot, Guolong Su, Nan Hua, Joshua Ainslie, Renshen Wang, Yasuhisa Fujii, Tomas Pfister:
FormNet: Structural Encoding beyond Sequential Modeling in Form Document Information Extraction. ACL (1) 2022: 3735-3754 - [c37]Sana Tonekaboni, Chun-Liang Li, Sercan Ö. Arik, Anna Goldenberg, Tomas Pfister:
Decoupling Local and Global Representations of Time Series. AISTATS 2022: 8700-8714 - [c36]Yuliang Zou, Zizhao Zhang, Chun-Liang Li, Han Zhang, Tomas Pfister, Jia-Bin Huang:
Learning Instance-Specific Adaptation for Cross-Domain Segmentation. ECCV (33) 2022: 459-476 - [c35]Asma Ghandeharioun, Been Kim, Chun-Liang Li, Brendan Jou, Brian Eoff, Rosalind W. Picard:
DISSECT: Disentangled Simultaneous Explanations via Concept Traversals. ICLR 2022 - [i42]Sana Tonekaboni, Chun-Liang Li, Sercan Ö. Arik, Anna Goldenberg, Tomas Pfister:
Decoupling Local and Global Representations of Time Series. CoRR abs/2202.02262 (2022) - [i41]Chen-Yu Lee, Chun-Liang Li, Timothy Dozat, Vincent Perot, Guolong Su, Nan Hua, Joshua Ainslie, Renshen Wang, Yasuhisa Fujii, Tomas Pfister:
FormNet: Structural Encoding beyond Sequential Modeling in Form Document Information Extraction. CoRR abs/2203.08411 (2022) - [i40]Yuliang Zou, Zizhao Zhang, Chun-Liang Li, Han Zhang, Tomas Pfister, Jia-Bin Huang:
Learning Instance-Specific Adaptation for Cross-Domain Segmentation. CoRR abs/2203.16530 (2022) - [i39]Kuniaki Saito, Kihyuk Sohn, Xiang Zhang, Chun-Liang Li, Chen-Yu Lee, Kate Saenko, Tomas Pfister:
Prefix Conditioning Unifies Language and Label Supervision. CoRR abs/2206.01125 (2022) - [i38]Jinsung Yoon, Kihyuk Sohn, Chun-Liang Li, Sercan Ö. Arik, Tomas Pfister:
SPADE: Semi-supervised Anomaly Detection under Distribution Mismatch. CoRR abs/2212.00173 (2022) - [i37]Songwei Ge, Shlok Mishra, Simon Kornblith, Chun-Liang Li, David Jacobs:
Hyperbolic Contrastive Learning for Visual Representations beyond Objects. CoRR abs/2212.00653 (2022) - 2021
- [j5]Sercan Ö. Arik
, Joel Shor, Rajarishi Sinha
, Jinsung Yoon, Joseph R. Ledsam
, Long T. Le, Michael W. Dusenberry, Nathanael C. Yoder
, Kris Popendorf, Arkady Epshteyn, Johan Euphrosine, Elli Kanal, Isaac Jones, Chun-Liang Li, Beth Luan, Joe Mckenna, Vikas Menon, Shashank Singh, Mimi Sun, Ashwin Sura Ravi, Leyou Zhang
, Dario Sava, Kane Cunningham, Hiroki Kayama, Thomas C. Tsai
, Daisuke Yoneoka
, Shuhei Nomura
, Hiroaki Miyata, Tomas Pfister:
A prospective evaluation of AI-augmented epidemiology to forecast COVID-19 in the USA and Japan. npj Digit. Medicine 4 (2021) - [j4]Haoran You
, Yu Cheng, Tianheng Cheng, Chun-Liang Li, Pan Zhou
:
Bayesian Cycle-Consistent Generative Adversarial Networks via Marginalizing Latent Sampling. IEEE Trans. Neural Networks Learn. Syst. 32(10): 4389-4403 (2021) - [c34]Chen-Yu Lee, Chun-Liang Li, Chu Wang, Renshen Wang, Yasuhisa Fujii, Siyang Qin, Ashok C. Popat, Tomas Pfister:
ROPE: Reading Order Equivariant Positional Encoding for Graph-based Document Information Extraction. ACL/IJCNLP (2) 2021: 314-321 - [c33]Chun-Liang Li, Kihyuk Sohn, Jinsung Yoon, Tomas Pfister:
CutPaste: Self-Supervised Learning for Anomaly Detection and Localization. CVPR 2021: 9664-9674 - [c32]Kibok Lee, Yian Zhu, Kihyuk Sohn, Chun-Liang Li, Jinwoo Shin, Honglak Lee:
i-Mix: A Domain-Agnostic Strategy for Contrastive Representation Learning. ICLR 2021 - [c31]Kihyuk Sohn, Chun-Liang Li, Jinsung Yoon, Minho Jin, Tomas Pfister:
Learning and Evaluating Representations for Deep One-Class Classification. ICLR 2021 - [c30]Yuliang Zou, Zizhao Zhang, Han Zhang, Chun-Liang Li, Xiao Bian, Jia-Bin Huang, Tomas Pfister:
PseudoSeg: Designing Pseudo Labels for Semantic Segmentation. ICLR 2021 - [c29]Sangwoo Mo, Hyunwoo Kang, Kihyuk Sohn, Chun-Liang Li, Jinwoo Shin:
Object-aware Contrastive Learning for Debiased Scene Representation. NeurIPS 2021: 12251-12264 - [c28]Songwei Ge, Shlok Mishra, Chun-Liang Li, Haohan Wang, David Jacobs:
Robust Contrastive Learning Using Negative Samples with Diminished Semantics. NeurIPS 2021: 27356-27368 - [c27]Si-An Chen, Chun-Liang Li, Hsuan-Tien Lin:
A Unified View of cGANs with and without Classifiers. NeurIPS 2021: 27566-27579 - [c26]Chenghui Zhou, Chun-Liang Li, Barnabás Póczos:
Unsupervised program synthesis for images by sampling without replacement. UAI 2021: 408-418 - [i36]Chun-Liang Li, Kihyuk Sohn, Jinsung Yoon, Tomas Pfister:
CutPaste: Self-Supervised Learning for Anomaly Detection and Localization. CoRR abs/2104.04015 (2021) - [i35]Asma Ghandeharioun, Been Kim, Chun-Liang Li, Brendan Jou, Brian Eoff, Rosalind W. Picard:
DISSECT: Disentangled Simultaneous Explanations via Concept Traversals. CoRR abs/2105.15164 (2021) - [i34]Jinsung Yoon, Kihyuk Sohn, Chun-Liang Li, Sercan Ö. Arik, Chen-Yu Lee, Tomas Pfister:
Self-Trained One-class Classification for Unsupervised Anomaly Detection. CoRR abs/2106.06115 (2021) - [i33]Chen-Yu Lee, Chun-Liang Li, Chu Wang, Renshen Wang, Yasuhisa Fujii, Siyang Qin, Ashok C. Popat, Tomas Pfister:
ROPE: Reading Order Equivariant Positional Encoding for Graph-based Document Information Extraction. CoRR abs/2106.10786 (2021) - [i32]Sangwoo Mo, Hyunwoo Kang, Kihyuk Sohn, Chun-Liang Li, Jinwoo Shin:
Object-aware Contrastive Learning for Debiased Scene Representation. CoRR abs/2108.00049 (2021) - [i31]Songwei Ge, Shlok Mishra, Haohan Wang, Chun-Liang Li, David Jacobs:
Robust Contrastive Learning Using Negative Samples with Diminished Semantics. CoRR abs/2110.14189 (2021) - [i30]Si-An Chen, Chun-Liang Li, Hsuan-Tien Lin:
A Unified View of cGANs with and without Classifiers. CoRR abs/2111.01035 (2021) - [i29]Si-An Chen, Chun-Liang Li, Hsuan-Tien Lin:
Improving Model Compatibility of Generative Adversarial Networks by Boundary Calibration. CoRR abs/2111.02316 (2021) - [i28]Kihyuk Sohn, Jinsung Yoon, Chun-Liang Li, Chen-Yu Lee, Tomas Pfister:
Anomaly Clustering: Grouping Images into Coherent Clusters of Anomaly Types. CoRR abs/2112.11573 (2021) - 2020
- [b1]Chun-Liang Li:
Learning Generative Models using Transformations. Carnegie Mellon University, USA, 2020 - [c25]Sercan Ömer Arik, Chun-Liang Li, Jinsung Yoon, Rajarishi Sinha, Arkady Epshteyn, Long T. Le, Vikas Menon, Shashank Singh, Leyou Zhang, Martin Nikoltchev, Yash Sonthalia, Hootan Nakhost, Elli Kanal, Tomas Pfister:
Interpretable Sequence Learning for Covid-19 Forecasting. NeurIPS 2020 - [c24]Kihyuk Sohn, David Berthelot, Nicholas Carlini, Zizhao Zhang, Han Zhang, Colin Raffel, Ekin Dogus Cubuk, Alexey Kurakin, Chun-Liang Li:
FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence. NeurIPS 2020 - [c23]Chih-Kuan Yeh, Been Kim, Sercan Ömer Arik, Chun-Liang Li, Tomas Pfister, Pradeep Ravikumar:
On Completeness-aware Concept-Based Explanations in Deep Neural Networks. NeurIPS 2020 - [i27]Kihyuk Sohn, David Berthelot, Chun-Liang Li, Zizhao Zhang, Nicholas Carlini, Ekin D. Cubuk, Alex Kurakin, Han Zhang, Colin Raffel:
FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence. CoRR abs/2001.07685 (2020) - [i26]Chenghui Zhou, Chun-Liang Li, Barnabás Póczos:
Unsupervised Program Synthesis for Images using Tree-Structured LSTM. CoRR abs/2001.10119 (2020) - [i25]Kihyuk Sohn, Zizhao Zhang, Chun-Liang Li, Han Zhang, Chen-Yu Lee, Tomas Pfister:
A Simple Semi-Supervised Learning Framework for Object Detection. CoRR abs/2005.04757 (2020) - [i24]Wei-Cheng Chang, Chun-Liang Li, Youssef Mroueh, Yiming Yang:
Kernel Stein Generative Modeling. CoRR abs/2007.03074 (2020) - [i23]Sercan Ömer Arik, Chun-Liang Li, Jinsung Yoon, Rajarishi Sinha, Arkady Epshteyn, Long T. Le, Vikas Menon, Shashank Singh, Leyou Zhang, Nate Yoder, Martin Nikoltchev, Yash Sonthalia, Hootan Nakhost, Elli Kanal, Tomas Pfister:
Interpretable Sequence Learning for COVID-19 Forecasting. CoRR abs/2008.00646 (2020) - [i22]Kibok Lee, Yian Zhu, Kihyuk Sohn, Chun-Liang Li, Jinwoo Shin, Honglak Lee:
i-Mix: A Strategy for Regularizing Contrastive Representation Learning. CoRR abs/2010.08887 (2020) - [i21]Yuliang Zou, Zizhao Zhang, Han Zhang, Chun-Liang Li, Xiao Bian, Jia-Bin Huang, Tomas Pfister:
PseudoSeg: Designing Pseudo Labels for Semantic Segmentation. CoRR abs/2010.09713 (2020) - [i20]Kihyuk Sohn, Chun-Liang Li, Jinsung Yoon, Minho Jin, Tomas Pfister:
Learning and Evaluating Representations for Deep One-class Classification. CoRR abs/2011.02578 (2020)
2010 – 2019
- 2019
- [c22]Chun-Liang Li, Wei-Cheng Chang, Youssef Mroueh, Yiming Yang, Barnabás Póczos:
Implicit Kernel Learning. AISTATS 2019: 2007-2016 - [c21]Chun-Liang Li, Tomas Simon, Jason M. Saragih, Barnabás Póczos, Yaser Sheikh:
LBS Autoencoder: Self-Supervised Fitting of Articulated Meshes to Point Clouds. CVPR 2019: 11967-11976 - [c20]Wei-Cheng Chang, Chun-Liang Li, Yiming Yang, Barnabás Póczos:
Kernel Change-point Detection with Auxiliary Deep Generative Models. ICLR (Poster) 2019 - [c19]Chun-Liang Li, Manzil Zaheer, Yang Zhang, Barnabás Póczos, Ruslan Salakhutdinov:
Point Cloud GAN. DGS@ICLR 2019 - [c18]Hsueh-Ti Derek Liu, Michael Tao, Chun-Liang Li, Derek Nowrouzezahrai, Alec Jacobson:
Beyond Pixel Norm-Balls: Parametric Adversaries using an Analytically Differentiable Renderer. ICLR (Poster) 2019 - [i19]Wei-Cheng Chang, Chun-Liang Li, Yiming Yang, Barnabás Póczos:
Kernel Change-point Detection with Auxiliary Deep Generative Models. CoRR abs/1901.06077 (2019) - [i18]Chun-Liang Li, Wei-Cheng Chang, Youssef Mroueh, Yiming Yang, Barnabás Póczos:
Implicit Kernel Learning. CoRR abs/1902.10214 (2019) - [i17]Chun-Liang Li, Tomas Simon, Jason M. Saragih, Barnabás Póczos, Yaser Sheikh:
LBS Autoencoder: Self-supervised Fitting of Articulated Meshes to Point Clouds. CoRR abs/1904.10037 (2019) - [i16]Songwei Ge, Austin Dill, Eunsu Kang, Chun-Liang Li, Lingyao Zhang, Manzil Zaheer, Barnabás Póczos:
Developing Creative AI to Generate Sculptural Objects. CoRR abs/1908.07587 (2019) - [i15]Chih-Kuan Yeh, Been Kim, Sercan Ömer Arik, Chun-Liang Li, Pradeep Ravikumar, Tomas Pfister:
On Concept-Based Explanations in Deep Neural Networks. CoRR abs/1910.07969 (2019) - [i14]Austin Dill, Chun-Liang Li, Songwei Ge, Eunsu Kang:
Getting Topology and Point Cloud Generation to Mesh. CoRR abs/1912.03787 (2019) - [i13]Austin Dill, Songwei Ge, Eunsu Kang, Chun-Liang Li, Barnabás Póczos:
Learned Interpolation for 3D Generation. CoRR abs/1912.10787 (2019) - 2018
- [c17]Yusha Liu, Chun-Liang Li, Barnabás Póczos:
Classifier Two Sample Test for Video Anomaly Detections. BMVC 2018: 71 - [c16]Youssef Mroueh, Chun-Liang Li, Tom Sercu, Anant Raj, Yu Cheng:
Sobolev GAN. ICLR (Poster) 2018 - [c15]Shashank Singh, Ananya Uppal, Boyue Li, Chun-Liang Li, Manzil Zaheer, Barnabás Póczos:
Nonparametric Density Estimation under Adversarial Losses. NeurIPS 2018: 10246-10257 - [i12]Xi Ouyang, Yu Cheng, Yifan Jiang, Chun-Liang Li, Pan Zhou:
Pedestrian-Synthesis-GAN: Generating Pedestrian Data in Real Scene and Beyond. CoRR abs/1804.02047 (2018) - [i11]Shashank Singh, Ananya Uppal, Boyue Li, Chun-Liang Li, Manzil Zaheer, Barnabás Póczos:
Nonparametric Density Estimation under Adversarial Losses. CoRR abs/1805.08836 (2018) - [i10]Hsueh-Ti Derek Liu, Michael Tao, Chun-Liang Li, Derek Nowrouzezahrai, Alec Jacobson:
Adversarial Geometry and Lighting using a Differentiable Renderer. CoRR abs/1808.02651 (2018) - [i9]Chun-Liang Li, Manzil Zaheer, Yang Zhang, Barnabás Póczos, Ruslan Salakhutdinov:
Point Cloud GAN. CoRR abs/1810.05795 (2018) - [i8]Chun-Liang Li, Eunsu Kang, Songwei Ge, Lingyao Zhang, Austin Dill, Manzil Zaheer, Barnabás Póczos:
Hallucinating Point Cloud into 3D Sculptural Object. CoRR abs/1811.05389 (2018) - [i7]Haoran You, Yu Cheng, Tianheng Cheng, Chun-Liang Li, Pan Zhou:
Bayesian CycleGAN via Marginalizing Latent Sampling. CoRR abs/1811.07465 (2018) - 2017
- [c14]Po-Wei Wang, Chun-Liang Li, J. Zico Kolter:
Polynomial Optimization Methods for Matrix Factorization. AAAI 2017: 2710-2717 - [c13]Jen-Hao Rick Chang, Chun-Liang Li, Barnabás Póczos, B. V. K. Vijaya Kumar
:
One Network to Solve Them All - Solving Linear Inverse Problems Using Deep Projection Models. ICCV 2017: 5889-5898 - [c12]Wei-Cheng Chang, Chun-Liang Li, Yiming Yang, Barnabás Póczos:
Data-driven Random Fourier Features using Stein Effect. IJCAI 2017: 1497-1503 - [c11]Chun-Liang Li, Wei-Cheng Chang, Yu Cheng, Yiming Yang, Barnabás Póczos:
MMD GAN: Towards Deeper Understanding of Moment Matching Network. NIPS 2017: 2203-2213 - [i6]Jen-Hao Rick Chang, Chun-Liang Li, Barnabás Póczos, B. V. K. Vijaya Kumar, Aswin C. Sankaranarayanan:
One Network to Solve Them All - Solving Linear Inverse Problems using Deep Projection Models. CoRR abs/1703.09912 (2017) - [i5]Wei-Cheng Chang, Chun-Liang Li, Yiming Yang, Barnabás Póczos:
Data-driven Random Fourier Features using Stein Effect. CoRR abs/1705.08525 (2017) - [i4]Chun-Liang Li, Wei-Cheng Chang, Yu Cheng, Yiming Yang, Barnabás Póczos:
MMD GAN: Towards Deeper Understanding of Moment Matching Network. CoRR abs/1705.08584 (2017) - [i3]Youssef Mroueh, Chun-Liang Li, Tom Sercu, Anant Raj, Yu Cheng:
Sobolev GAN. CoRR abs/1711.04894 (2017) - 2016
- [c10]Chun-Liang Li, Hsuan-Tien Lin, Chi-Jen Lu:
Rivalry of Two Families of Algorithms for Memory-Restricted Streaming PCA. AISTATS 2016: 473-481 - [c9]Chun-Liang Li, Kirthevasan Kandasamy, Barnabás Póczos, Jeff G. Schneider:
High Dimensional Bayesian Optimization via Restricted Projection Pursuit Models. AISTATS 2016: 884-892 - [c8]Chun-Liang Li, Barnabás Póczos:
Utilize Old Coordinates: Faster Doubly Stochastic Gradients for Kernel Methods. UAI 2016 - [i2]Chun-Liang Li, Siamak Ravanbakhsh, Barnabás Póczos:
Annealing Gaussian into ReLU: a New Sampling Strategy for Leaky-ReLU RBM. CoRR abs/1611.03879 (2016) - 2015
- [j3]Chun-Liang Li, Yu-Chuan Su, Ting-Wei Lin, Cheng-Hao Tsai, Wei-Cheng Chang, Kuan-Hao Huang, Tzu-Ming Kuo, Shan-Wei Lin, Young-San Lin, Yu-Chen Lu, Chun-Pai Yang, Cheng-Xia Chang, Wei-Sheng Chin, Yu-Chin Juan, Hsiao-Yu Tung, Jui-Pin Wang, Cheng-Kuang Wei, Felix Wu, Tu-Chun Yin, Tong Yu, Yong Zhuang, Shou-De Lin, Hsuan-Tien Lin, Chih-Jen Lin:
Combination of feature engineering and ranking models for paper-author identification in KDD cup 2013. J. Mach. Learn. Res. 16: 2921-2947 (2015) - [j2]Chun-Liang Li, Chun-Sung Ferng, Hsuan-Tien Lin
:
Active Learning Using Hint Information. Neural Comput. 27(8): 1738-1765 (2015) - [i1]Chun-Liang Li, Hsuan-Tien Lin, Chi-Jen Lu:
Rivalry of Two Families of Algorithms for Memory-Restricted Streaming PCA. CoRR abs/1506.01490 (2015) - 2014
- [j1]Wei-Sheng Chin, Yong Zhuang, Yu-Chin Juan, Felix Wu, Hsiao-Yu Tung, Tong Yu, Jui-Pin Wang, Cheng-Xia Chang, Chun-Pai Yang, Wei-Cheng Chang, Kuan-Hao Huang, Tzu-Ming Kuo, Shan-Wei Lin, Young-San Lin, Yu-Chen Lu, Yu-Chuan Su, Cheng-Kuang Wei, Tu-Chun Yin, Chun-Liang Li, Ting-Wei Lin, Cheng-Hao Tsai, Shou-De Lin, Hsuan-Tien Lin, Chih-Jen Lin:
Effective string processing and matching for author disambiguation. J. Mach. Learn. Res. 15(1): 3037-3064 (2014) - [c7]Jyun-Yu Jiang, Chun-Liang Li, Chun-Pai Yang, Chung-Tsai Su:
POSTER: Scanning-free Personalized Malware Warning System by Learning Implicit Feedback from Detection Logs. CCS 2014: 1436-1438 - [c6]Chun-Liang Li, Hsuan-Tien Lin:
Condensed Filter Tree for Cost-Sensitive Multi-Label Classification. ICML 2014: 423-431 - 2013
- [c5]Chun-Liang Li, Yu-Chuan Su, Ting-Wei Lin, Cheng-Hao Tsai, Wei-Cheng Chang, Kuan-Hao Huang
, Tzu-Ming Kuo, Shan-Wei Lin, Young-San Lin, Yu-Chen Lu, Chun-Pai Yang, Cheng-Xia Chang, Wei-Sheng Chin, Yu-Chin Juan, Hsiao-Yu Tung, Jui-Pin Wang, Cheng-Kuang Wei, Felix Wu, Tu-Chun Yin, Tong Yu, Yong Zhuang, Shou-de Lin
, Hsuan-Tien Lin
, Chih-Jen Lin
:
Combination of feature engineering and ranking models for paper-author identification in KDD Cup 2013. KDD Cup 2013: 2:1-2:7 - [c4]Wei-Sheng Chin, Yu-Chin Juan, Yong Zhuang, Felix Wu, Hsiao-Yu Tung, Tong Yu, Jui-Pin Wang, Cheng-Xia Chang, Chun-Pai Yang, Wei-Cheng Chang, Kuan-Hao Huang
, Tzu-Ming Kuo, Shan-Wei Lin, Young-San Lin, Yu-Chen Lu, Yu-Chuan Su, Cheng-Kuang Wei, Tu-Chun Yin, Chun-Liang Li, Ting-Wei Lin, Cheng-Hao Tsai, Shou-De Lin
, Hsuan-Tien Lin
, Chih-Jen Lin
:
Effective string processing and matching for author disambiguation. KDD Cup 2013: 7:1-7:9 - 2012
- [c3]Po-Lung Chen, Chen-Tse Tsai, Yao-Nan Chen, Ku-Chun Chou, Chun-Liang Li, Cheng-Hao Tsai, Kuan-Wei Wu, Yu-Cheng Chou, Chung-Yi Li, Wei-Shih Lin, Shu-Hao Yu, Rong-Bing Chiu, Chieh-Yen Lin, Chien-Chih Wang, Po-Wei Wang, Wei-Lun Su, Chen-Hung Wu, Tsung-Ting Kuo, Todd G. McKenzie, Ya-Hsuan Chang, Chun-Sung Ferng, Chia-Mau Ni, Hsuan-Tien Lin, Chih-Jen Lin, Shou-De Lin:
A Linear Ensemble of Individual and Blended Models for Music Rating Prediction. KDD Cup 2012: 21-60 - [c2]Todd G. McKenzie, Chun-Sung Ferng, Yao-Nan Chen, Chun-Liang Li, Cheng-Hao Tsai, Kuan-Wei Wu, Ya-Hsuan Chang, Chung-Yi Li, Wei-Shih Lin, Shu-Hao Yu, Chieh-Yen Lin, Po-Wei Wang, Chia-Mau Ni, Wei-Lun Su, Tsung-Ting Kuo, Chen-Tse Tsai, Po-Lung Chen, Rong-Bing Chiu, Ku-Chun Chou, Yu-Cheng Chou, Chien-Chih Wang, Chen-Hung Wu, Hsuan-Tien Lin, Chih-Jen Lin, Shou-De Lin:
Novel Models and Ensemble Techniques to Discriminate Favorite Items from Unrated Ones for Personalized Music Recommendation. KDD Cup 2012: 101-135 - [c1]Chun-Liang Li, Chun-Sung Ferng, Hsuan-Tien Lin:
Active Learning with Hinted Support Vector Machine. ACML 2012: 221-235
Coauthor Index

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