Mitigating Gradient Bias in Multi-objective Learning: A Provably Convergent Stochastic Approach. - Heshan Devaka Fernando; Han Shen; Miao Liu 001; Subhajit Chaudhury; Keerthiram Murugesan; Tianyi Chen (CoRR, 2022)

On the Stability Analysis of Open Federated Learning Systems. - Youbang Sun; Heshan Devaka Fernando; Tianyi Chen; Shahin Shahrampour (ACC, 2023)

Mitigating Gradient Bias in Multi-objective Learning: A Provably Convergent Approach. - Heshan Devaka Fernando; Han Shen; Miao Liu 001; Subhajit Chaudhury; Keerthiram Murugesan; Tianyi Chen (ICLR, 2023)

Variance Reduction Can Improve Trade-Off in Multi-Objective Learning. - Heshan Devaka Fernando; Lisha Chen; Songtao Lu; Pin-Yu Chen; Miao Liu 001; Subhajit Chaudhury; Keerthiram Murugesan; Gaowen Liu; Meng Wang 003; Tianyi Chen (ICASSP, 2024)

SF-DQN: Provable Knowledge Transfer using Successor Feature for Deep Reinforcement Learning. - Shuai Zhang 015; Heshan Devaka Fernando; Miao Liu 001; Keerthiram Murugesan; Songtao Lu; Pin-Yu Chen; Tianyi Chen; Meng Wang 003 (ICML, 2024)

Mitigating Forgetting in LLM Supervised Fine-Tuning and Preference Learning. - Heshan Devaka Fernando; Han Shen; Parikshit Ram; Yi Zhou 015; Horst Samulowitz; Nathalie Baracaldo; Tianyi Chen (CoRR, 2024)

Three-Way Trade-Off in Multi-Objective Learning: Optimization, Generalization and Conflict-Avoidance. - Lisha Chen; Heshan Devaka Fernando; Yiming Ying; Tianyi Chen (J. Mach. Learn. Res., 2024)