118 citations · 148 across the 21 of their papers we have counts for
3 papers · 1 filter
Near-Optimal Sample Complexity for Recursive Entropic Risk Reinforcement Learning with a Generative Model
Amirparsa Bahrami, Oliver Mortensen, Mohammad Sadegh Talebi
In this paper, we study the sample complexities of value and policy learning in finite discounted Markov decision processes (MDPs) under recursive entropic risk preferences with ri…
Randomized Least Squares Value Iteration itself is Joint Differentially Private
Haiyang Lu, Pratik Gajane, Shaojie Bai +1
As reinforcement learning (RL) increasingly applies to sensitive domains, such as health care and recommendation systems, privacy-preserving techniques have become essential to pro…
On the Sample Complexity of Discounted Reinforcement Learning with Optimized Certainty Equivalents
Oliver Mortensen, Mohammad Sadegh Talebi
We study risk-sensitive reinforcement learning in finite discounted MDPs, where a generative model of the MDP is assumed to be available. We consider a family or risk measures call…