2 citations · 3 across the 6 of their papers we have counts for
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cs.IR2023
Optimizing Long-term Value for Auction-Based Recommender Systems via On-Policy Reinforcement Learning
Ruiyang Xu, Jalaj Bhandari, Dmytro Korenkevych +4
Auction-based recommender systems are prevalent in online advertising platforms, but they are typically optimized to allocate recommendation slots based on immediate expected retur…
cs.IR2023★ 1 cited
Evaluating Online Bandit Exploration In Large-Scale Recommender System
Hongbo Guo, Ruben Naeff, Alex Nikulkov +1
Bandit learning has been an increasingly popular design choice for recommender system. Despite the strong interest in bandit learning from the community, there remains multiple bot…