Education

Selected Awards

IBM Ph.D. Fellowship, 2018

Best student paper runner-up, International Joint Conference on Artificial Intelligence (IJCAI), 2017

First Places, Track 1 and Track 2 of KDD Cup 2013

First Places, Track 1 and Track 2 of KDD Cup 2011

Publications (* denotes equal contribution)

• CutPaste: Self-Supervised Learning for Anomaly Detection and Localization
  Chun-Liang Li*, Kihyuk Sohn*, Jinsung Yoon, and Tomas Pfister
  To appear in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021
• Learning and Evaluating Representations for Deep One-class Classification
  Kihyuk Sohn*, Chun-Liang Li*, Jinsung Yoon, Minho Jin, and Tomas Pfister
  In International Conference on Learning Representations (ICLR), 2021 [code]
• PseudoSeg: Designing Pseudo Labels for Semantic Segmentation
  Yuliang Zou, Zizhao Zhang, Han Zhang, Chun-Liang Li, Xiao Bian, Jia-Bin Huang, and Tomas Pfister
  In International Conference on Learning Representations (ICLR), 2021 [code]
• i-Mix: A Domain-Agnostic Strategy for Contrastive Representation Learning
  Kibok Lee, Yian Zhu, Kihyuk Sohn, Chun-Liang Li, Jinwoo Shin, and Honglak Lee
  In International Conference on Learning Representations (ICLR), 2021 [code]
• Interpretable Sequence Learning for Covid-19 Forecasting
  Sercan Arik, Chun-Liang Li, Jinsung Yoon, Rajarishi Sinha, Arkady Epshteyn, Long Le, Vikas Menon, Shashank Singh, Leyou Zhang, Nate Yoder, Martin Nikoltchev, Yash Sonthalia, Hootan Nakhost, Elli Kanal and Tomas Pfister
  In Advances in Neural Information Processing Systems (NeurIPS), 2020 (Spotlight)
• FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence
  Kihyuk Sohn, David Berthelot, Chun-Liang Li, Zizhao Zhang, Nicholas Carlini, Ekin D. Cubuk, Alex Kurakin, Han Zhang and Colin Raffel
  In Advances in Neural Information Processing Systems (NeurIPS), 2020
• On Completeness-aware Concept-Based Explanations in Deep Neural Networks
  Chih-Kuan Yeh, Been Kim, Sercan Arik, Chun-Liang Li, Tomas Pfister and Pradeep Ravikumar
  In Advances in Neural Information Processing Systems (NeurIPS), 2020
• Learning Generative Models using Transformations
  Chun-Liang Li
  PhD Thesis, Carnegie Mellon University, 2019
• LBS Autoencoder: Self-supervised Fitting of Articulated Meshes to Point Clouds
  Chun-Liang Li, Tomas Simon, Jason Saragih, Barnabás Póczos and Yaser Sheikh
  In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019 [video]
• Implicit Kernel Learning
  Chun-Liang Li, Wei-Chen Chang, Youssef Mroueh, Yiming Yang and Barnabás Póczos
  In Proceedings of the International Conference on Artificial Intelligence and Statistic (AISTATS), 2019
• Kernel Change-Point Detection with Auxiliary Deep Generative Models
  Wei-Chen Chang, Chun-Liang Li, Yiming Yang and Barnabás Póczos
  In Proceedings of the International Conference on Learning Representations (ICLR), 2019 [code]
• Beyond Pixel Norm-Balls: Parametric Adversaries using an Analytically Differentiable Renderer
  Hsueh-Ti Liu, Michael Tao, Chun-Liang Li, Derek Nowrouzezahrai and Alec Jacobson
  In Proceedings of the International Conference on Learning Representations (ICLR), 2019
• Point Cloud GAN
  Chun-Liang Li, Manzil Zaheer, Yang Zhang, Barnabás Póczos and Ruslan Salakhutdinov
  In ICLR Workshop on Deep Generative Models for Highly Structured Data, 2019 [code]
• Nonparametric Density Estimation with Adversarial Losses
  Shashank Singh, Ananya Uppal, Boyue Li, Chun-Liang Li, Manzil Zaheer and Barnabás Póczos
  In Advances in Neural Information Processing Systems (NIPS), 2018
• Classifier Two-Sample Test for Video Anomaly Detections
  Yusha Liu*, Chun-Liang Li*, and Barnabás Póczos
  In Processings of the British Machine Vision Conference (BMVC), 2018 [code]
• Sobolev GAN
  Youssef Mroueh, Chun-Liang Li*, Tom Sercu*, Anant Raj*, and Yu Cheng
  In International Conference on Learning Representations (ICLR), 2018 [code]
• CMU DeepLens: Deep Learning For Automatic Image-based Galaxy-Galaxy Strong Lens Finding
  Francois Lanusse, Quanbin Ma, Nan Li, Thomas E. Collett, Chun-Liang Li, Siamak Ravanbakhsh, Rachel Mandelbaum and Barnabás Póczos
  In Monthly Notices of the Royal Astronomical Society (MNRAS), 2018. [code]
• MMD GAN: Towards Deeper Understanding of Moment Matching Network
  Chun-Liang Li*, Wei-Chen Chang*, Yu Cheng, Yiming Yang and Barnabás Póczos
  In Advances in Neural Information Processing Systems (NIPS), 2017 [code]
• GAN Connoisseur: Can GANs Learn Simple 1D Parametric Distributions?
  Manzil Zaheer*, Chun-Liang Li*, Barnabás Póczos and Ruslan Salakhutdinov
  In NIPS Workshop on Deep Learning: Bridging Theory and Practice, 2017
• One Network to Solve Them All — Solving Linear Inverse Problems using Deep Projection Models
  J. H. Rick Chang, Chun-Liang Li, Barnabás Póczos, B. V. K. Vijaya Kumar and Aswin C. Sankaranarayanan
  In Proceedings of the International Conference on Computer Vision (ICCV), 2017 (Oral) [code]
• Data-driven Random Fourier Feature using Stein Effect
  Wei-Chen Chang, Chun-Liang Li, Yiming Yang and Barnabás Póczos
  In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), 2017
  (Best student paper runner-up)
• Polynomial Optimization Methods for Matrix Factorization
  Po-Wei Wang, Chun-Liang Li, and J. Zico Kolter
  In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2017
• Utilize Old Coordinates: Faster Doubly Stochastic Gradients for Kernel Methods
  Chun-Liang Li and Barnabás Póczos
  In Proceedings of the Uncertainty in Artificial Intelligence (UAI), 2016
• High Dimensional Bayesian Optimization via Restricted Projection Pursuit Models
  Chun-Liang Li, Kirthevasan Kandasamy, Barnabás Póczos and Jeff Schneider
  In Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS), 2016
• Rivalry of Two Families of Algorithms for Memory-Restricted Streaming PCA
  Chun-Liang Li, Hsuan-Tien Lin and Chi-Jen Lu
  In Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS), 2016
• Active Learning with Hint Information
  Chun-Liang Li, Chun-Sung Ferng, and Hsuan-Tien Lin
  In Neural Computation, 2015
• Combination of Feature Engineering and Ranking Models for Paper-Author Identification in KDD Cup 2013
  C.-L. Li, Y.-C. Su, T.-W. Lin, C.-H. Tsai, W.-C. Chang, K.-H. Huang, T.-M. Kuo, S.-W. Lin, Y.-S. Lin, Y.-C. Lu, C.-P. Yang, C.-X. Chang, W.-S. Chin, Y.-C. Juan, H.-Y. Tung, J.-P. Wang, C.-K. Wei, F. Wu, T.-C. Yin, T. Yu, Y. Zhuang, S.-D. Lin, H.-T. Lin and C.-J. Lin
  In Journal of Machine Learning Research, 2015 (Extended first-place winner report of KDD Cup 2013 track 1)
• Effective String Processing and Matching for Author Disambiguation
  W.-S. Chin, Y.-C. Juan, Y. Zhuang, F. Wu, H.-Y. Tung, T. Yu, J.-P. Wang, C.-X. Chang, C.-P. Yang, W.-C. Chang, K.-H. Huang, T.-M. Kuo, S.-W. Lin, Y.-S. Lin, Y.-C. Lu, Y.-C. Su, C.-K. Wei, T.-C. Yin, C.-L. Li, T.-W. Lin, C.-H. Tsai, S.-D. Lin, H.-T. Lin and C.-J. Lin
  In Journal of Machine Learning Research, 2014 (Extended first-place winner report of KDD Cup 2013 track 2)
• POSTER: Scanning-free Personalized Malware Warning System by Learning Implicit Feedback from Detection Logs
  Jyun-Yu Jiang, Chun-Liang Li, Chun-Pai Yang and Chung-Tsai Su
  In Proceedings of the ACM Conference on Computer and Communications Security (CCS), 2014
• Condensed Filter Tree for Cost-Sensitive Multi-Label Classification
  Chun-Liang Li and Hsuan-Tien Lin
  In Proceedings of the International Conference on Machine Learning (ICML), 2014 [slide]
• Active Learning with Hinted Support Vector Machine
  Chun-Liang Li, Chun-Sung Ferng, and Hsuan-Tien Lin
  In Proceedings of the Asian Conference on Machine Learning (ACML), 2012 [slide]
• A Linear Ensemble of Individual and Blended Models for Music Rating Prediction
  P.-L. Chen, C.-T. Tsai, Y.-N. Chen, K.-C. Chou, C.-L. Li, C.-H. Tsai, K.-W. Wu, Y.-C. Chou, C.-Y. Li, W.-S. Lin, S.-H. Yu, R.-B. Chiu, C.-Y. Lin, C.-C. Wang, P.-W. Wang, W.-L. Su, C.-H. Wu, T.-T. Kuo, T. G. McKenzie, Y.-H. Chang, C.-S. Ferng, C.-M. Ni, H.-T. Lin, C.-J. Lin and S.-D. Lin
  In Proceedings of the KDD Cup 2011 Workshop, 2012
• Novel Models and Ensemble Techniques to Discriminate Favorite Items from Unrated Ones for Personalized Music Recommendation
  T. G. McKenzie, C.-S. Ferng, Y.-N. Chen, C.-L. Li, C.-H. Tsai, K.-W. Wu, Y.-H. Chang, C.-Y. Li, W.-S. Lin, S.-H. Yu, C.-Y. Lin, P.-W. Wang, C.-M. Ni, W.-L. Su, T.-T. Kuo, C.-T. Tsai, P.-L. Chen, R.-B. Chiu, K.-C. Chou, Y.-C. Chou, C.-C. Wang, C.-H. Wu, H.-T. Lin, C.-J. Lin and S.-D. Lin
  In Proceedings of the KDD Cup 2011 Workshop, 2012