Ju, Peizhong

13 publications

ICLR 2025 Broadening Target Distributions for Accelerated Diffusion Models via a Novel Analysis Approach Yuchen Liang, Peizhong Ju, Yingbin Liang, Ness Shroff

ICML 2025 FSL-SAGE: Accelerating Federated Split Learning via Smashed Activation Gradient Estimation Srijith Nair, Michael Lin, Peizhong Ju, Amirreza Talebi, Elizabeth Serena Bentley, Jia Liu

ICLR 2025 How to Find the Exact Pareto Front for Multi-Objective MDPs? Yining Li, Peizhong Ju, Ness Shroff

AAAI 2025 PSMGD: Periodic Stochastic Multi-Gradient Descent for Fast Multi-Objective Optimization Mingjing Xu, Peizhong Ju, Jia Liu, Haibo Yang

ICLR 2025 Theory on Score-Mismatched Diffusion Models and Zero-Shot Conditional Samplers Yuchen Liang, Peizhong Ju, Yingbin Liang, Ness Shroff

ICML 2025 Unlocking the Power of Rehearsal in Continual Learning: A Theoretical Perspective Junze Deng, Qinhang Wu, Peizhong Ju, Sen Lin, Yingbin Liang, Ness Shroff

ICLR 2024 Achieving Fairness in Multi-Agent MDP Using Reinforcement Learning Peizhong Ju, Arnob Ghosh, Ness Shroff

ICLR 2024 Achieving Sample and Computational Efficient Reinforcement Learning by Action Space Reduction via Grouping Yining Li, Peizhong Ju, Ness Shroff

ICLR 2023 Theoretical Characterization of the Generalization Performance of Overfitted Meta-Learning Peizhong Ju, Yingbin Liang, Ness Shroff

ICML 2023 Theory on Forgetting and Generalization of Continual Learning Sen Lin, Peizhong Ju, Yingbin Liang, Ness Shroff

NeurIPS 2022 On the Generalization Power of the Overfitted Three-Layer Neural Tangent Kernel Model Peizhong Ju, Xiaojun Lin, Ness Shroff

ICML 2021 On the Generalization Power of Overfitted Two-Layer Neural Tangent Kernel Models Peizhong Ju, Xiaojun Lin, Ness Shroff

NeurIPS 2020 Overfitting Can Be Harmless for Basis Pursuit, but Only to a Degree Peizhong Ju, Xiaojun Lin, Jia Liu