Yifei Min | DeepAI

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Featured Co-authors

Michael I. Jordan
283 publications
Quanquan Gu
124 publications
Zhaoran Wang
121 publications
Zhuoran Yang
110 publications
Lin Chen
100 publications
S. Kevin Zhou
90 publications
Chen Feng
84 publications
Amin Karbasi
77 publications
Mikhail Belkin
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Tianhao Wang
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James S. Duncan
43 publications

∙ 05/10/2023

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

We study multi-agent reinforcement learning in the setting of episodic M...

3 Yifei Min, et al. ∙

∙ 04/06/2023

Implicit Anatomical Rendering for Medical Image Segmentation with Stochastic Experts

Integrating high-level semantically correlated contents and low-level an...

0 Chenyu You, et al. ∙

∙ 04/05/2023

ACTION++: Improving Semi-supervised Medical Image Segmentation with Adaptive Anatomical Contrast

Medical data often exhibits long-tail distributions with heavy class imb...

0 Chenyu You, et al. ∙

∙ 02/03/2023

Rethinking Semi-Supervised Medical Image Segmentation: A Variance-Reduction Perspective

For medical image segmentation, contrastive learning is the dominant pra...

0 Chenyu You, et al. ∙

∙ 07/07/2022

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

We study federated contextual linear bandits, where M agents cooperate w...

6 Jiafan He, et al. ∙

∙ 05/26/2022

Pessimism in the Face of Confounders: Provably Efficient Offline Reinforcement Learning in Partially Observable Markov Decision Processes

We study offline reinforcement learning (RL) in partially observable Mar...

6 Miao Lu, et al. ∙

∙ 03/07/2022

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

We study a Markov matching market involving a planner and a set of strat...

2 Yifei Min, et al. ∙

∙ 10/25/2021

Learning Stochastic Shortest Path with Linear Function Approximation

We study the stochastic shortest path (SSP) problem in reinforcement lea...

11 Yifei Min, et al. ∙

∙ 06/22/2021

Variance-Aware Off-Policy Evaluation with Linear Function Approximation

We study the off-policy evaluation (OPE) problem in reinforcement learni...

7 Yifei Min, et al. ∙

∙ 08/03/2020

Multiple Descent: Design Your Own Generalization Curve

This paper explores the generalization loss of linear regression in vari...

2 Lin Chen, et al. ∙

∙ 02/25/2020

The Curious Case of Adversarially Robust Models: More Data Can Help, Double Descend, or Hurt Generalization

Despite remarkable success, deep neural networks are sensitive to human-...

10 Yifei Min, et al. ∙

∙ 02/11/2020

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

Despite remarkable success in practice, modern machine learning models h...

38 Lin Chen, et al. ∙

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