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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
Group Distributionally Robust Optimization with Flexible Sample Queries
Haomin Bai, Dingzhi Yu, Shuai Li +2
Group distributionally robust optimization (GDRO) aims to develop models that perform well across distributions simultaneously. Existing GDRO algorithms can only process a fixe…
cs.LG2025
Cascading Bandits Robust to Adversarial Corruptions
Jize Xie, Cheng Chen, Zhiyong Wang +1
Online learning to rank sequentially recommends a small list of items to users from a large candidate set and receives the users' click feedback. In many real-world scenarios, user…