6 citations · 22 across the 11 of their papers we have counts for
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cs.LG2023★ 2 cited
Unified Off-Policy Learning to Rank: a Reinforcement Learning Perspective
Zeyu Zhang, Yi Su, Hui Yuan +5
Off-policy Learning to Rank (LTR) aims to optimize a ranker from data collected by a deployed logging policy. However, existing off-policy learning to rank methods often make stron…
cs.LG2023★ 1 cited
Adversarial Attacks on Online Learning to Rank with Stochastic Click Models
Zichen Wang, Rishab Balasubramanian, Hui Yuan +3
We propose the first study of adversarial attacks on online learning to rank. The goal of the adversary is to misguide the online learning to rank algorithm to place the target ite…