| 2024 | CVPR | 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 |
| 2023 | AISTATS | Finding Regularized Competitive Equilibria of Heterogeneous Agent Macroeconomic Models via Reinforcement Learning. | Ruitu Xu, Yifei Min, Tianhao Wang, Michael I. Jordan, Zhaoran Wang, Zhuoran Yang |
| 2023 | ICLR | Pessimism in the Face of Confounders: Provably Efficient Offline Reinforcement Learning in Partially Observable Markov Decision Processes. | Miao Lu, Yifei Min, Zhaoran Wang, Zhuoran Yang |
| 2023 | ICML | Cooperative Multi-Agent Reinforcement Learning: Asynchronous Communication and Linear Function Approximation. | Yifei Min, Jiafan He, Tianhao Wang, Quanquan Gu |
| 2023 | MICCAI | Implicit Anatomical Rendering for Medical Image Segmentation with Stochastic Experts. | Chenyu You, Weicheng Dai, Yifei Min, Lawrence H. Staib, James S. Duncan |
| 2023 | MICCAI | 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 |
| 2022 | ICML | Learning Stochastic Shortest Path with Linear Function Approximation. | Yifei Min, Jiafan He, Tianhao Wang, Quanquan Gu |
| 2021 | UAI | The curious case of adversarially robust models: More data can help, double descend, or hurt generalization. | Yifei Min, Lin Chen, Amin Karbasi |
| 2020 | ICML | More Data Can Expand The Generalization Gap Between Adversarially Robust and Standard Models. | Lin Chen, Yifei Min, Mingrui Zhang, Amin Karbasi |