11 citations · 38 across the 10 of their papers we have counts for
10 papers
Taming Equilibrium Bias in Risk-Sensitive Multi-Agent Reinforcement Learning
Yingjie Fei, Ruitu Xu
We study risk-sensitive multi-agent reinforcement learning under general-sum Markov games, where agents optimize the entropic risk measure of rewards with possibly diverse risk pre…
Don't Retrain, Just Rewrite: Countering Adversarial Perturbations by Rewriting Text
Ashim Gupta, Carter Wood Blum, Temma Choji +4
Can language models transform inputs to protect text classifiers against adversarial attacks? In this work, we present ATINTER, a model that intercepts and learns to rewrite advers…
Cascaded Gaps: Towards Gap-Dependent Regret for Risk-Sensitive Reinforcement Learning
Yingjie Fei, Ruitu Xu
In this paper, we study gap-dependent regret guarantees for risk-sensitive reinforcement learning based on the entropic risk measure. We propose a novel definition of sub-optimalit…
Exponential Bellman Equation and Improved Regret Bounds for Risk-Sensitive Reinforcement Learning
Yingjie Fei, Zhuoran Yang, Yudong Chen +1
We study risk-sensitive reinforcement learning (RL) based on the entropic risk measure. Although existing works have established non-asymptotic regret guarantees for this problem,…
Dynamic Regret of Policy Optimization in Non-stationary Environments
Yingjie Fei, Zhuoran Yang, Zhaoran Wang +1
We consider reinforcement learning (RL) in episodic MDPs with adversarial full-information reward feedback and unknown fixed transition kernels. We propose two model-free policy op…
Risk-Sensitive Reinforcement Learning: Near-Optimal Risk-Sample Tradeoff in Regret
Yingjie Fei, Zhuoran Yang, Yudong Chen +2
We study risk-sensitive reinforcement learning in episodic Markov decision processes with unknown transition kernels, where the goal is to optimize the total reward under the risk…
Spectral Frank-Wolfe Algorithm: Strict Complementarity and Linear Convergence
Lijun Ding, Yingjie Fei, Qiantong Xu +1
We develop a novel variant of the classical Frank-Wolfe algorithm, which we call spectral Frank-Wolfe, for convex optimization over a spectrahedron. The spectral Frank-Wolfe algori…
Achieving the Bayes Error Rate in Synchronization and Block Models by SDP, Robustly
Yingjie Fei, Yudong Chen
We study the statistical performance of semidefinite programming (SDP) relaxations for clustering under random graph models. Under the Synchronization model, Censo…
Hidden Integrality and Semi-random Robustness of SDP Relaxation for Sub-Gaussian Mixture Model
Yingjie Fei, Yudong Chen
We consider the problem of estimating the discrete clustering structures under the Sub-Gaussian Mixture Model. Our main results establish a hidden integrality property of a semidef…
Exponential error rates of SDP for block models: Beyond Grothendieck's inequality
Yingjie Fei, Yudong Chen
In this paper we consider the cluster estimation problem under the Stochastic Block Model. We show that the semidefinite programming (SDP) formulation for this problem achieves an…