Beyond H-Divergence: Domain Adaptation Theory With Jensen-Shannon Divergence. - Changjian Shui; Qi Chen 015; Jun Wen; Fan Zhou 006; Christian Gagné 001; Boyu Wang 004 (CoRR, 2020)

Generalization Bounds For Meta-Learning: An Information-Theoretic Analysis. - Qi Chen 015; Changjian Shui; Mario Marchand (NeurIPS, 2021)

Fair Representation Learning through Implicit Path Alignment. - Changjian Shui; Qi Chen 015; Jiaqi Li 005; Boyu Wang 004; Christian Gagné 001 (ICML, 2022)

On Learning Fairness and Accuracy on Multiple Subgroups. - Changjian Shui; Gezheng Xu; Qi Chen 015; Jiaqi Li 005; Charles X. Ling; Tal Arbel; Boyu Wang 004; Christian Gagné 001 (NeurIPS, 2022)

A novel domain adaptation theory with Jensen-Shannon divergence. - Changjian Shui; Qi Chen 015; Jun Wen; Fan Zhou 006; Christian Gagné 001; Boyu Wang 004 (Knowl. Based Syst., 2022)

Algorithm-Dependent Bounds for Representation Learning of Multi-Source Domain Adaptation. - Qi Chen 015; Mario Marchand (AISTATS, 2023)

On the Stability-Plasticity Dilemma in Continual Meta-Learning: Theory and Algorithm. - Qi Chen 015; Changjian Shui; Ligong Han; Mario Marchand (NeurIPS, 2023)

Intersectional Unfairness Discovery. - Gezheng Xu; Qi Chen 015; Charles Ling 001; Boyu Wang 004; Changjian Shui (ICML, 2024)

Towards Understanding Evolving Patterns in Sequential Data. - Qiuhao Zeng; Long-Kai Huang; Qi Chen 015; Charles X. Ling; Boyu Wang 004 (NeurIPS, 2024)