331 citations · 712 across the 75 of their papers we have counts for
4 papers · 1 filter
Minimax Quantile Lower Bounds for Interactive Statistical Decision Making with Privacy
Raghav Bongole, Amirreza Zamani, Tobias J. Oechtering +1
Minimax risk and regret are expectation-based criteria and do not capture rare but consequential failures. To address this concern, we develop a -explicit minimax-quantile theor…
Instantiating Bayesian CVaR lower bounds in Interactive Decision Making Problems
Raghav Bongole, Tobias J. Oechtering, Mikael Skoglund
Recent work established a generalized-Fano framework for lower bounding prior-predictive (Bayesian) CVaR in interactive statistical decision making. In this paper, we show how to i…
Information-Theoretic Minimax Regret Bounds for Reinforcement Learning based on Duality
Raghav Bongole, Amaury Gouverneur, Borja Rodríguez-Gálvez +2
We study agents acting in an unknown environment where the agent's goal is to find a robust policy. We consider robust policies as policies that achieve high cumulative rewards for…
An Information-Theoretic Analysis of Bayesian Reinforcement Learning
Amaury Gouverneur, Borja Rodríguez-Gálvez, Tobias J. Oechtering +1
Building on the framework introduced by Xu and Raginksy [1] for supervised learning problems, we study the best achievable performance for model-based Bayesian reinforcement learni…