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cs.LG2025
Near-Optimal Regret for Efficient Stochastic Combinatorial Semi-Bandits
Zichun Ye, Runqi Wang, Xutong Liu +1
The combinatorial multi-armed bandit (CMAB) is a cornerstone of sequential decision-making framework, dominated by two algorithmic families: UCB-based and adversarial methods such…
cs.LG2025
Tight Gap-Dependent Memory-Regret Trade-Off for Single-Pass Streaming Stochastic Multi-Armed Bandits
Zichun Ye, Chihao Zhang, Jiahao Zhao
We study the problem of minimizing gap-dependent regret for single-pass streaming stochastic multi-armed bandits (MAB). In this problem, the arms are present in a stream, and a…