| 2021 | ICML | SparseBERT: Rethinking the Importance Analysis in Self-attention. | Han Shi, Jiahui Gao, Xiaozhe Ren, Hang Xu, Xiaodan Liang, Zhenguo Li, James Tin-Yau Kwok |
| 2020 | ICML | Searching to Exploit Memorization Effect in Learning with Noisy Labels. | Quanming Yao, Hansi Yang, Bo Han, Gang Niu, James Tin-Yau Kwok |
| 2019 | ICML | Efficient Nonconvex Regularized Tensor Completion with Structure-aware Proximal Iterations. | Quanming Yao, James Tin-Yau Kwok, Bo Han |
| 2018 | ICML | Lightweight Stochastic Optimization for Minimizing Finite Sums with Infinite Data. | Shuai Zheng, James Tin-Yau Kwok |
| 2018 | ICML | Online Convolutional Sparse Coding with Sample-Dependent Dictionary. | Yaqing Wang, Quanming Yao, James Tin-Yau Kwok, Lionel M. Ni |
| 2017 | AAAI | Efficient Sparse Low-Rank Tensor Completion Using the Frank-Wolfe Algorithm. | Xiawei Guo, Quanming Yao, James Tin-Yau Kwok |
| 2014 | AISTATS | Accelerated Stochastic Gradient Method for Composite Regularization. | Wenliang Zhong, James Tin-Yau Kwok |
| 2014 | ICML | Fast Stochastic Alternating Direction Method of Multipliers. | Wenliang Zhong, James Tin-Yau Kwok |
| 2013 | ICML | Efficient Multi-label Classification with Many Labels. | Wei Bi, James Tin-Yau Kwok |
| 2013 | ICML | Covariate Shift in Hilbert Space: A Solution via Sorrogate Kernels. | Kai Zhang, Vincent Wenchen Zheng, Qiaojun Wang, James Tin-Yau Kwok, Qiang Yang, Ivan Marsic |
| 2012 | ICML | Convex Multitask Learning with Flexible Task Clusters. | Wenliang Zhong, James Tin-Yau Kwok |
| 2009 | CVPR | Unsupervised Maximum Margin Feature Selection with manifold regularization. | Bin Zhao, James Tin-Yau Kwok, Fei Wang, Changshui Zhang |
| 2009 | ICDM | Maximum Margin Clustering with Multivariate Loss Function. | Bin Zhao, James Tin-Yau Kwok, Changshui Zhang |
| 2005 | AISTATS | Very Large SVM Training using Core Vector Machines. | Ivor W. Tsang, James Tin-Yau Kwok, Pak-Ming Cheung |
| 2005 | IJCNN | Pattern de-noising based on support vector data description. | Jooyoung Park, Daesung Kang, Jongho Kim, James Tin-Yau Kwok, Ivor Wai-Hung Tsang |
| 2005 | IJCNN | Kernel relevant component analysis for distance metric learning. | Ivor Wai-Hung Tsang, Pak-Ming Cheung, James Tin-Yau Kwok |
| 2001 | AISTATS | Bayesian Support Vector Regression. | Martin H. C. Law, James Tin-Yau Kwok |
| 2000 | CEC | An extended genetic rule induction algorithm. | J. Juan Liu, James Tin-Yau Kwok |
| 1999 | ESANN | Integrating the evidence framework and the support vector machine. | James Tin-Yau Kwok |
| 1999 | IJCNN | Moderating the outputs of support vector machine classifiers. | James Tin-Yau Kwok |
| 1998 | ICONIP | Automated Text Categorization Using Support Vector Machine. | James Tin-Yau Kwok |
| 1998 | ICPR | Support vector mixture for classification and regression problems. | James Tin-Yau Kwok |
| 1996 | ICANN | Bayesian Regularization in Constructive Neural Networks. | James Tin-Yau Kwok, Dit-Yan Yeung |