Yifei Min

According to our database, Yifei Min authored at least 19 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

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., December, 2024

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

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023

Finding Regularized Competitive Equilibria of Heterogeneous Agent Macroeconomic Models with Reinforcement Learning.

Ruitu Xu, Yifei Min, Tianhao Wang, Zhaoran Wang, Michael I. Jordan, Zhuoran Yang

CoRR, 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

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

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Noise-Adaptive Thompson Sampling for Linear Contextual Bandits.

Ruitu Xu, Yifei Min, Tianhao Wang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 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

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

Implicit Anatomical Rendering for Medical Image Segmentation with Stochastic Experts.

Chenyu You, Weicheng Dai, Yifei Min, Lawrence H. Staib, James S. Duncan

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023

Bootstrapping Semi-supervised Medical Image Segmentation with Anatomical-Aware Contrastive Distillation.

Chenyu You, Weicheng Dai, Yifei Min, Lawrence H. Staib, James S. Duncan

Proceedings of the Information Processing in Medical Imaging, 2023

Cooperative Multi-Agent Reinforcement Learning: Asynchronous Communication and Linear Function Approximation.

Yifei Min, Jiafan He, Tianhao Wang, Quanquan Gu

Proceedings of the International Conference on Machine Learning, 2023

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

Proceedings of the Eleventh International Conference on Learning Representations, 2023

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

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Learn to Match with No Regret: Reinforcement Learning in Markov Matching Markets.

Yifei Min, Tianhao Wang, Ruitu Xu, Zhaoran Wang, Michael I. Jordan, Zhuoran Yang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

A Simple and Provably Efficient Algorithm for Asynchronous Federated Contextual Linear Bandits.

Jiafan He, Tianhao Wang, Yifei Min, Quanquan Gu

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Learning Stochastic Shortest Path with Linear Function Approximation.

Yifei Min, Jiafan He, Tianhao Wang, Quanquan Gu

Proceedings of the International Conference on Machine Learning, 2022

2021

The curious case of adversarially robust models: More data can help, double descend, or hurt generalization.

Yifei Min, Lin Chen, Amin Karbasi

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Variance-Aware Off-Policy Evaluation with Linear Function Approximation.

Yifei Min, Tianhao Wang, Dongruo Zhou, Quanquan Gu

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Multiple Descent: Design Your Own Generalization Curve.

Lin Chen, Yifei Min, Mikhail Belkin, Amin Karbasi

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

More Data Can Expand The Generalization Gap Between Adversarially Robust and Standard Models.

Lin Chen, Yifei Min, Mingrui Zhang, Amin Karbasi

Proceedings of the 37th International Conference on Machine Learning, 2020