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cs.LG2026
One Good Source is All You Need: Near-Optimal Regret for Bandits under Heterogeneous Noise
Amith Bhat, Haipeng Luo, Aadirupa Saha
We study -armed Multiarmed Bandit (MAB) problem with heterogeneous data sources, each exhibiting unknown and distinct noise variances . The learner's obje…
cs.LG2024
Near-Optimal Regret in Linear MDPs with Aggregate Bandit Feedback
Asaf Cassel, Haipeng Luo, Aviv Rosenberg +1
In many real-world applications, it is hard to provide a reward signal in each step of a Reinforcement Learning (RL) process and more natural to give feedback when an episode ends.…