3 papers
cs.LG2025
Data-dependent Bounds with -Optimal Best-of-Both-Worlds Guarantees in Multi-Armed Bandits using Stability-Penalty Matching
Quan Nguyen, Shinji Ito, Junpei Komiyama +1
Existing data-dependent and best-of-both-worlds regret bounds for multi-armed bandits problems have limited adaptivity as they are either data-dependent but not best-of-both-worlds…
cs.LG2025
Beyond Minimax Rates in Group Distributionally Robust Optimization via a Novel Notion of Sparsity
Quan Nguyen, Nishant A. Mehta, Cristóbal Guzmán
The minimax sample complexity of group distributionally robust optimization (GDRO) has been determined up to a factor, where is the number of groups. In this work, we…
cs.LG2024
Near-optimal Per-Action Regret Bounds for Sleeping Bandits
Quan Nguyen, Nishant A. Mehta
We derive near-optimal per-action regret bounds for sleeping bandits, in which both the sets of available arms and their losses in every round are chosen by an adversary. In a sett…