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2020 – today
- 2025
[i15]Chenyu You, Haocheng Dai, Yifei Min, Jasjeet S. Sekhon, Sarang C. Joshi, James S. Duncan:
The Silent Majority: Demystifying Memorization Effect in the Presence of Spurious Correlations. CoRR abs/2501.00961 (2025)- 2024
- [j1]Chenyu You
, Weicheng Dai, Fenglin Liu, Yifei Min, Nicha C. Dvornek, Xiaoxiao Li, David A. Clifton, Lawrence H. Staib, James S. Duncan:
Mine yOur owN Anatomy: Revisiting Medical Image Segmentation With Extremely Limited Labels. IEEE Trans. Pattern Anal. Mach. Intell. 46(12): 11136-11151 (2024) - [c16]Chenyu You, Yifei Min, Weicheng Dai, Jasjeet S. Sekhon, Lawrence H. Staib, James S. Duncan:
Calibrating Multi-modal Representations: A Pursuit of Group Robustness without Annotations. CVPR 2024: 26140-26150 - [i14]Chenyu You, Yifei Min, Weicheng Dai, Jasjeet S. Sekhon, Lawrence H. Staib, James S. Duncan:
Calibrating Multi-modal Representations: A Pursuit of Group Robustness without Annotations. CoRR abs/2403.07241 (2024) - 2023
- [c15]Ruitu Xu, Yifei Min, Tianhao Wang, Michael I. Jordan, Zhaoran Wang, Zhuoran Yang:
Finding Regularized Competitive Equilibria of Heterogeneous Agent Macroeconomic Models via Reinforcement Learning. AISTATS 2023: 375-407 - [c14]Miao Lu, Yifei Min, Zhaoran Wang, Zhuoran Yang:
Pessimism in the Face of Confounders: Provably Efficient Offline Reinforcement Learning in Partially Observable Markov Decision Processes. ICLR 2023 - [c13]Yifei Min, Jiafan He, Tianhao Wang, Quanquan Gu:
Cooperative Multi-Agent Reinforcement Learning: Asynchronous Communication and Linear Function Approximation. ICML 2023: 24785-24811 - [c12]Chenyu You, Weicheng Dai, Yifei Min, Lawrence H. Staib, James S. Duncan:
Bootstrapping Semi-supervised Medical Image Segmentation with Anatomical-Aware Contrastive Distillation. IPMI 2023: 641-653 - [c11]Chenyu You, Weicheng Dai, Yifei Min, Lawrence H. Staib, Jasjeet S. Sekhon, James S. Duncan:
ACTION++: Improving Semi-supervised Medical Image Segmentation with Adaptive Anatomical Contrast. MICCAI (4) 2023: 194-205 - [c10]Chenyu You, Weicheng Dai, Yifei Min, Lawrence H. Staib, James S. Duncan:
Implicit Anatomical Rendering for Medical Image Segmentation with Stochastic Experts. MICCAI (3) 2023: 561-571 - [c9]Ruitu Xu, Yifei Min, Tianhao Wang:
Noise-Adaptive Thompson Sampling for Linear Contextual Bandits. NeurIPS 2023 - [c8]Chenyu You, Weicheng Dai, Yifei Min, Fenglin Liu, David A. Clifton, S. Kevin Zhou, Lawrence H. Staib, James S. Duncan:
Rethinking Semi-Supervised Medical Image Segmentation: A Variance-Reduction Perspective. NeurIPS 2023 - [i13]Chenyu You, Weicheng Dai, Yifei Min, Fenglin Liu, Xiaoran Zhang, Chen Feng, David A. Clifton, S. Kevin Zhou, Lawrence Hamilton Staib, James S. Duncan:
Rethinking Semi-Supervised Medical Image Segmentation: A Variance-Reduction Perspective. CoRR abs/2302.01735 (2023) - [i12]Ruitu Xu, Yifei Min, Tianhao Wang, Zhaoran Wang, Michael I. Jordan, Zhuoran Yang:
Finding Regularized Competitive Equilibria of Heterogeneous Agent Macroeconomic Models with Reinforcement Learning. CoRR abs/2303.04833 (2023) - [i11]Chenyu You, Weicheng Dai, Yifei Min, Lawrence H. Staib, Jasjeet S. Sekhon, James S. Duncan:
ACTION++: Improving Semi-supervised Medical Image Segmentation with Adaptive Anatomical Contrast. CoRR abs/2304.02689 (2023) - [i10]Chenyu You, Weicheng Dai, Yifei Min, Lawrence H. Staib, James S. Duncan:
Implicit Anatomical Rendering for Medical Image Segmentation with Stochastic Experts. CoRR abs/2304.03209 (2023) - [i9]Yifei Min, Jiafan He, Tianhao Wang, Quanquan Gu:
Cooperative Multi-Agent Reinforcement Learning: Asynchronous Communication and Linear Function Approximation. CoRR abs/2305.06446 (2023) - 2022
- [c7]Yifei Min, Jiafan He, Tianhao Wang, Quanquan Gu:
Learning Stochastic Shortest Path with Linear Function Approximation. ICML 2022: 15584-15629 - [c6]Jiafan He, Tianhao Wang, Yifei Min, Quanquan Gu:
A Simple and Provably Efficient Algorithm for Asynchronous Federated Contextual Linear Bandits. NeurIPS 2022 - [c5]Yifei Min, Tianhao Wang, Ruitu Xu, Zhaoran Wang, Michael I. Jordan, Zhuoran Yang:
Learn to Match with No Regret: Reinforcement Learning in Markov Matching Markets. NeurIPS 2022 - [i8]Yifei Min, Tianhao Wang, Ruitu Xu, Zhaoran Wang, Michael I. Jordan, Zhuoran Yang:
Learn to Match with No Regret: Reinforcement Learning in Markov Matching Markets. CoRR abs/2203.03684 (2022) - [i7]Miao Lu, Yifei Min, Zhaoran Wang, Zhuoran Yang:
Pessimism in the Face of Confounders: Provably Efficient Offline Reinforcement Learning in Partially Observable Markov Decision Processes. CoRR abs/2205.13589 (2022) - [i6]Jiafan He, Tianhao Wang, Yifei Min, Quanquan Gu:
A Simple and Provably Efficient Algorithm for Asynchronous Federated Contextual Linear Bandits. CoRR abs/2207.03106 (2022) - 2021
- [c4]Yifei Min, Tianhao Wang, Dongruo Zhou, Quanquan Gu:
Variance-Aware Off-Policy Evaluation with Linear Function Approximation. NeurIPS 2021: 7598-7610 - [c3]Lin Chen, Yifei Min, Mikhail Belkin, Amin Karbasi:
Multiple Descent: Design Your Own Generalization Curve. NeurIPS 2021: 8898-8912 - [c2]Yifei Min, Lin Chen, Amin Karbasi:
The curious case of adversarially robust models: More data can help, double descend, or hurt generalization. UAI 2021: 129-139 - [i5]Yifei Min, Tianhao Wang, Dongruo Zhou, Quanquan Gu:
Variance-Aware Off-Policy Evaluation with Linear Function Approximation. CoRR abs/2106.11960 (2021) - [i4]Yifei Min, Jiafan He, Tianhao Wang, Quanquan Gu:
Learning Stochastic Shortest Path with Linear Function Approximation. CoRR abs/2110.12727 (2021) - 2020
- [c1]Lin Chen, Yifei Min, Mingrui Zhang, Amin Karbasi:
More Data Can Expand The Generalization Gap Between Adversarially Robust and Standard Models. ICML 2020: 1670-1680 - [i3]Lin Chen, Yifei Min, Mingrui Zhang, Amin Karbasi:
More Data Can Expand the Generalization Gap Between Adversarially Robust and Standard Models. CoRR abs/2002.04725 (2020) - [i2]Yifei Min, Lin Chen, Amin Karbasi:
The Curious Case of Adversarially Robust Models: More Data Can Help, Double Descend, or Hurt Generalization. CoRR abs/2002.11080 (2020) - [i1]Lin Chen, Yifei Min, Mikhail Belkin, Amin Karbasi:
Multiple Descent: Design Your Own Generalization Curve. CoRR abs/2008.01036 (2020)
Coauthor Index
aka: Lawrence Hamilton Staib
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