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cs.IR2024
Mitigating Exposure Bias in Online Learning to Rank Recommendation: A Novel Reward Model for Cascading Bandits
Masoud Mansoury, Bamshad Mobasher, Herke van Hoof
Exposure bias is a well-known issue in recommender systems where items and suppliers are not equally represented in the recommendation results. This bias becomes particularly probl…
cs.LG2024
Planning with a Learned Policy Basis to Optimally Solve Complex Tasks
Guillermo Infante, David Kuric, Anders Jonsson +2
Conventional reinforcement learning (RL) methods can successfully solve a wide range of sequential decision problems. However, learning policies that can generalize predictably acr…