More Data Can Expand The Generalization Gap Between Adversarially Robust and Standard Models. - Lin Chen 003; Yifei Min; Mingrui Zhang; Amin Karbasi (ICML, 2020)

Multiple Descent: Design Your Own Generalization Curve. - Lin Chen 003; Yifei Min; Mikhail Belkin; Amin Karbasi (NeurIPS, 2021)

Variance-Aware Off-Policy Evaluation with Linear Function Approximation. - Yifei Min; Tianhao Wang 002; Dongruo Zhou; Quanquan Gu (NeurIPS, 2021)

The curious case of adversarially robust models: More data can help, double descend, or hurt generalization. - Yifei Min; Lin Chen 003; Amin Karbasi (UAI, 2021)

Learning Stochastic Shortest Path with Linear Function Approximation. - Yifei Min; Jiafan He; Tianhao Wang 002; Quanquan Gu (ICML, 2022)

A Simple and Provably Efficient Algorithm for Asynchronous Federated Contextual Linear Bandits. - Jiafan He; Tianhao Wang 002; Yifei Min; Quanquan Gu (NeurIPS, 2022)

Learn to Match with No Regret: Reinforcement Learning in Markov Matching Markets. - Yifei Min; Tianhao Wang 002; Ruitu Xu; Zhaoran Wang 001; Michael I. Jordan; Zhuoran Yang (NeurIPS, 2022)

Finding Regularized Competitive Equilibria of Heterogeneous Agent Macroeconomic Models via Reinforcement Learning. - Ruitu Xu; Yifei Min; Tianhao Wang 002; Michael I. Jordan; Zhaoran Wang 001; Zhuoran Yang (AISTATS, 2023)

Pessimism in the Face of Confounders: Provably Efficient Offline Reinforcement Learning in Partially Observable Markov Decision Processes. - Miao Lu; Yifei Min; Zhaoran Wang 001; Zhuoran Yang (ICLR, 2023)

Cooperative Multi-Agent Reinforcement Learning: Asynchronous Communication and Linear Function Approximation. - Yifei Min; Jiafan He; Tianhao Wang 002; Quanquan Gu (ICML, 2023)

Bootstrapping Semi-supervised Medical Image Segmentation with Anatomical-Aware Contrastive Distillation. - Chenyu You; Weicheng Dai; Yifei Min; Lawrence H. Staib; James S. Duncan (IPMI, 2023)

Implicit Anatomical Rendering for Medical Image Segmentation with Stochastic Experts. - Chenyu You; Weicheng Dai; Yifei Min; Lawrence H. Staib; James S. Duncan (MICCAI (3), 2023)

ACTION++: Improving Semi-supervised Medical Image Segmentation with Adaptive Anatomical Contrast. - Chenyu You; Weicheng Dai; Yifei Min; Lawrence H. Staib; Jasjeet S. Sekhon; James S. Duncan (MICCAI (4), 2023)

Noise-Adaptive Thompson Sampling for Linear Contextual Bandits. - Ruitu Xu; Yifei Min; Tianhao Wang 002 (NeurIPS, 2023)

Rethinking Semi-Supervised Medical Image Segmentation: A Variance-Reduction Perspective. - Chenyu You; Weicheng Dai; Yifei Min; Fenglin Liu; David A. Clifton; S. Kevin Zhou; Lawrence H. Staib; James S. Duncan (NeurIPS, 2023)

Rethinking Semi-Supervised Medical Image Segmentation: A Variance-Reduction Perspective. - Chenyu You; Weicheng Dai; Yifei Min; Fenglin Liu; Xiaoran Zhang; Chen Feng; David A. Clifton; S. Kevin Zhou; Lawrence Hamilton Staib; James S. Duncan (CoRR, 2023)

Finding Regularized Competitive Equilibria of Heterogeneous Agent Macroeconomic Models with Reinforcement Learning. - Ruitu Xu; Yifei Min; Tianhao Wang 002; Zhaoran Wang 001; Michael I. Jordan; Zhuoran Yang (CoRR, 2023)

Calibrating Multi-modal Representations: A Pursuit of Group Robustness without Annotations. - Chenyu You; Yifei Min; Weicheng Dai; Jasjeet S. Sekhon; Lawrence H. Staib; James S. Duncan (CVPR, 2024)

Mine yOur owN Anatomy: Revisiting Medical Image Segmentation With Extremely Limited Labels. - Chenyu You; Weicheng Dai; Fenglin Liu; Yifei Min; Nicha C. Dvornek; Xiaoxiao Li; David A. Clifton; Lawrence H. Staib; James S. Duncan (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

The Silent Majority: Demystifying Memorization Effect in the Presence of Spurious Correlations. - Chenyu You; Haocheng Dai; Yifei Min; Jasjeet S. Sekhon; Sarang C. Joshi; James S. Duncan (CoRR, 2025)