4 citations · 8 across the 8 of their papers we have counts for
4 papers · 1 filter
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…
Learn to Match with No Regret: Reinforcement Learning in Markov Matching Markets
Yifei Min, Tianhao Wang, Ruitu Xu +3
We study a Markov matching market involving a planner and a set of strategic agents on the two sides of the market. At each step, the agents are presented with a dynamical context,…
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…
Learning the Kernel for Classification and Regression
Chen Li, Luca Venturi, Ruitu Xu
We investigate a series of learning kernel problems with polynomial combinations of base kernels, which will help us solve regression and classification problems. We also perform s…