Yifei Min
13 papers · 2020–2024 · 6 venues · across top CS/AI venues
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Achievements
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🌍 Conference Polyglot · Silver 🌉 Interdisciplinary Bridge · Silver 🗺️ Taxonomy Completionist (27) 👑 Triple Crown 🗃️ Keyword Collector (55)
🔥
Unstoppable · Bronze
⚡
Prolific Year · Productive
💎
Century Club · Bronze
Top co-authors
Research topics
Machine Learning
(13)
Learning Types
(10)
Optimization & Theory
(8)
Reinforcement Learning
(6)
Methods
(6)
Artificial Intelligence
(5)
Core AI
(4)
Applications
(3)
Mathematics & Optimization
(2)
Core Methods
(2)
Optimization
(2)
Computer Vision
(1)
Application Areas
(1)
Bayesian & Probabilistic · Artificial Intelligence
(1)
Bayesian & Probabilistic · Machine Learning
(1)
Keywords
regret bound
(5)
reinforcement learning
(4)
linear function approximation
(3)
double descent
(2)
contrastive learning
(2)
adversarial training
(2)
value iteration
(2)
variance reduction
(2)
asynchronous communication
(2)
adversarial robustness
(2)
contextual bandit
(2)
communication complexity
(1)
semi-supervised learning
(1)
function approximation
(1)
bayesian inference
(1)
multi-agent reinforcement learning
(1)
domain generalization
(1)
generalization error
(1)
offline reinforcement learning
(1)
partially observable markov decision process
(1)
Papers
Calibrating Multi-modal Representations: A Pursuit of Group Robustness without Annotations
CVPR 2024
Cooperative Multi-Agent Reinforcement Learning: Asynchronous Communication and Linear Function Approximation
ICML 2023
Finding Regularized Competitive Equilibria of Heterogeneous Agent Macroeconomic Models via Reinforcement Learning
AISTATS 2023
Noise-Adaptive Thompson Sampling for Linear Contextual Bandits
NeurIPS 2023
Pessimism in the Face of Confounders: Provably Efficient Offline Reinforcement Learning in Partially Observable Markov Decision Processes
ICLR 2023
Rethinking Semi-Supervised Medical Image Segmentation: A Variance-Reduction Perspective
NeurIPS 2023
A Simple and Provably Efficient Algorithm for Asynchronous Federated Contextual Linear Bandits
NeurIPS 2022
Learning Stochastic Shortest Path with Linear Function Approximation
ICML 2022
Learn to Match with No Regret: Reinforcement Learning in Markov Matching Markets
NeurIPS 2022
Multiple Descent: Design Your Own Generalization Curve
NeurIPS 2021
The curious case of adversarially robust models: More data can help, double descend, or hurt generalization
UAI 2021
Variance-Aware Off-Policy Evaluation with Linear Function Approximation
NeurIPS 2021
More Data Can Expand The Generalization Gap Between Adversarially Robust and Standard Models
ICML 2020