Yifei Min - RankMe

32 papers A* 11A 2Journal 16Unranked 3

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	The Silent Majority: Demystifying Memorization Effect in the Presence of Spurious Correlations. CoRR Chenyu You, Haocheng Dai, Yifei Min, Jasjeet S. Sekhon, Sarang C. Joshi, James S. Duncan
2024	A*	`conf`	Calibrating Multi-modal Representations: A Pursuit of Group Robustness without Annotations. CVPR Chenyu You, Yifei Min, Weicheng Dai, Jasjeet S. Sekhon, Lawrence H. Staib, James S. Duncan
2024	J	`jnl`	Calibrating Multi-modal Representations: A Pursuit of Group Robustness without Annotations. CoRR Chenyu You, Yifei Min, Weicheng Dai, Jasjeet S. Sekhon, Lawrence H. Staib, James S. Duncan
2024	J	`jnl`	Mine yOur owN Anatomy: Revisiting Medical Image Segmentation With Extremely Limited Labels. IEEE Trans. Pattern Anal. Mach. Intell. Chenyu You, Weicheng Dai, Fenglin Liu, Yifei Min, Nicha C. Dvornek, Xiaoxiao Li, David A. Clifton, Lawrence H. Staib, James S. Duncan
2023	—	`conf`	ACTION++: Improving Semi-supervised Medical Image Segmentation with Adaptive Anatomical Contrast. MICCAI (4) Chenyu You, Weicheng Dai, Yifei Min, Lawrence H. Staib, Jasjeet S. Sekhon, James S. Duncan
2023	J	`jnl`	ACTION++: Improving Semi-supervised Medical Image Segmentation with Adaptive Anatomical Contrast. CoRR Chenyu You, Weicheng Dai, Yifei Min, Lawrence H. Staib, Jasjeet S. Sekhon, James S. Duncan
2023	—	`conf`	Bootstrapping Semi-supervised Medical Image Segmentation with Anatomical-Aware Contrastive Distillation. IPMI Chenyu You, Weicheng Dai, Yifei Min, Lawrence H. Staib, James S. Duncan
2023	A*	`conf`	Cooperative Multi-Agent Reinforcement Learning: Asynchronous Communication and Linear Function Approximation. ICML Yifei Min, Jiafan He, Tianhao Wang, Quanquan Gu
2023	J	`jnl`	Cooperative Multi-Agent Reinforcement Learning: Asynchronous Communication and Linear Function Approximation. CoRR Yifei Min, Jiafan He, Tianhao Wang, Quanquan Gu
2023	A	`conf`	Finding Regularized Competitive Equilibria of Heterogeneous Agent Macroeconomic Models via Reinforcement Learning. AISTATS Ruitu Xu, Yifei Min, Tianhao Wang, Michael I. Jordan, Zhaoran Wang, Zhuoran Yang
2023	J	`jnl`	Finding Regularized Competitive Equilibria of Heterogeneous Agent Macroeconomic Models with Reinforcement Learning. CoRR Ruitu Xu, Yifei Min, Tianhao Wang, Zhaoran Wang, Michael I. Jordan, Zhuoran Yang
2023	—	`conf`	Implicit Anatomical Rendering for Medical Image Segmentation with Stochastic Experts. MICCAI (3) Chenyu You, Weicheng Dai, Yifei Min, Lawrence H. Staib, James S. Duncan
2023	J	`jnl`	Implicit Anatomical Rendering for Medical Image Segmentation with Stochastic Experts. CoRR Chenyu You, Weicheng Dai, Yifei Min, Lawrence H. Staib, James S. Duncan
2023	A*	`conf`	Noise-Adaptive Thompson Sampling for Linear Contextual Bandits. NeurIPS Ruitu Xu, Yifei Min, Tianhao Wang
2023	A*	`conf`	Pessimism in the Face of Confounders: Provably Efficient Offline Reinforcement Learning in Partially Observable Markov Decision Processes. ICLR Miao Lu, Yifei Min, Zhaoran Wang, Zhuoran Yang
2023	A*	`conf`	Rethinking Semi-Supervised Medical Image Segmentation: A Variance-Reduction Perspective. NeurIPS Chenyu You, Weicheng Dai, Yifei Min, Fenglin Liu, David A. Clifton, S. Kevin Zhou, Lawrence H. Staib, James S. Duncan
2023	J	`jnl`	Rethinking Semi-Supervised Medical Image Segmentation: A Variance-Reduction Perspective. CoRR Chenyu You, Weicheng Dai, Yifei Min, Fenglin Liu, Xiaoran Zhang, Chen Feng, David A. Clifton, S. Kevin Zhou, Lawrence Hamilton Staib, James S. Duncan
2022	A*	`conf`	A Simple and Provably Efficient Algorithm for Asynchronous Federated Contextual Linear Bandits. NeurIPS Jiafan He, Tianhao Wang, Yifei Min, Quanquan Gu
2022	J	`jnl`	A Simple and Provably Efficient Algorithm for Asynchronous Federated Contextual Linear Bandits. CoRR Jiafan He, Tianhao Wang, Yifei Min, Quanquan Gu
2022	A*	`conf`	Learn to Match with No Regret: Reinforcement Learning in Markov Matching Markets. NeurIPS Yifei Min, Tianhao Wang, Ruitu Xu, Zhaoran Wang, Michael I. Jordan, Zhuoran Yang
2022	J	`jnl`	Learn to Match with No Regret: Reinforcement Learning in Markov Matching Markets. CoRR Yifei Min, Tianhao Wang, Ruitu Xu, Zhaoran Wang, Michael I. Jordan, Zhuoran Yang
2022	A*	`conf`	Learning Stochastic Shortest Path with Linear Function Approximation. ICML Yifei Min, Jiafan He, Tianhao Wang, Quanquan Gu
2022	J	`jnl`	Pessimism in the Face of Confounders: Provably Efficient Offline Reinforcement Learning in Partially Observable Markov Decision Processes. CoRR Miao Lu, Yifei Min, Zhaoran Wang, Zhuoran Yang
2021	J	`jnl`	Learning Stochastic Shortest Path with Linear Function Approximation. CoRR Yifei Min, Jiafan He, Tianhao Wang, Quanquan Gu
2021	A*	`conf`	Multiple Descent: Design Your Own Generalization Curve. NeurIPS Lin Chen, Yifei Min, Mikhail Belkin, Amin Karbasi
2021	A	`conf`	The curious case of adversarially robust models: More data can help, double descend, or hurt generalization. UAI Yifei Min, Lin Chen, Amin Karbasi
2021	A*	`conf`	Variance-Aware Off-Policy Evaluation with Linear Function Approximation. NeurIPS Yifei Min, Tianhao Wang, Dongruo Zhou, Quanquan Gu
2021	J	`jnl`	Variance-Aware Off-Policy Evaluation with Linear Function Approximation. CoRR Yifei Min, Tianhao Wang, Dongruo Zhou, Quanquan Gu
2020	A*	`conf`	More Data Can Expand The Generalization Gap Between Adversarially Robust and Standard Models. ICML Lin Chen, Yifei Min, Mingrui Zhang, Amin Karbasi
2020	J	`jnl`	More Data Can Expand the Generalization Gap Between Adversarially Robust and Standard Models. CoRR Lin Chen, Yifei Min, Mingrui Zhang, Amin Karbasi
2020	J	`jnl`	Multiple Descent: Design Your Own Generalization Curve. CoRR Lin Chen, Yifei Min, Mikhail Belkin, Amin Karbasi
2020	J	`jnl`	The Curious Case of Adversarially Robust Models: More Data Can Help, Double Descend, or Hurt Generalization. CoRR Yifei Min, Lin Chen, Amin Karbasi