2 citations · 3 across the 8 of their papers we have counts for
8 papers
EVaR-Optimal Arm Identification in Bandits
Mehrasa Ahmadipour, Aurélien Garivier
We study the fixed-confidence best arm identification (BAI) problem within the multi-armed bandit (MAB) framework under the Entropic Value-at-Risk (EVaR) criterion. Our analysis co…
Identifying the Best Transition Law
Mehrasa Ahmadipour, élise Crepon, Aurélien Garivier
Motivated by recursive learning in Markov Decision Processes, this paper studies best-arm identification in bandit problems where each arm's reward is drawn from a multinomial dist…
Efficient Risk-sensitive Planning via Entropic Risk Measures
Alexandre Marthe, Samuel Bounan, Aurélien Garivier +1
Risk-sensitive planning aims to identify policies maximizing some tail-focused metrics in Markov Decision Processes (MDPs). Such an optimization task can be very costly for the mos…
Sequential Learning of the Pareto Front for Multi-objective Bandits
Elise Crépon, Aurélien Garivier, Wouter M Koolen
We study the problem of sequential learning of the Pareto front in multi-objective multi-armed bandits. An agent is faced with K possible arms to pull. At each turn she picks one,…
On Sparsity and Sub-Gaussianity in the Johnson-Lindenstrauss Lemma
Aurélien Garivier, Emmanuel Pilliat
We provide a simple proof of the Johnson-Lindenstrauss lemma for sub-Gaussian variables. We extend the analysis to identify how sparse projections can be, and what the cost of spar…
Beyond Average Return in Markov Decision Processes
Alexandre Marthe, Aurélien Garivier, Claire Vernade
What are the functionals of the reward that can be computed and optimized exactly in Markov Decision Processes?In the finite-horizon, undiscounted setting, Dynamic Programming (DP)…