Chun-Liang Li
李俊良
I am a research scientist at Google. I received my PhD in Machine Learning from Carnegie Mellon University supervised by Prof. Barnabás Póczos. Prior to joining CMU, I received my B.S. and M.S. degree at National Taiwan University under supervision of Prof. Hsuan-Tien Lin. I enjoy working with students and learning from them. Please feel free to drop me an email if you are interested in an internship or collaborating with me.
Contact
Education
2014/09 -- 2019/08
Carnegie Mellon University, Pittsburgh, USA
Ph.D. in Machine Learning Department
2008/09 -- 2013/06
National Taiwan University, Taipei, Taiwan
B.S. / M.S. in Computer Science and Information Engineering
Selected Awards
Publications (* denotes equal contribution)
- 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 Strategy for Regularizing 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 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