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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…
cs.LG2022
Simultaneously Learning Stochastic and Adversarial Bandits under the Position-Based Model
Cheng Chen, Canzhe Zhao, Shuai Li
Online learning to rank (OLTR) interactively learns to choose lists of items from a large collection based on certain click models that describe users' click behaviors. Most recent…