186 citations · 210 across the 15 of their papers we have counts for
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cs.LG2022
Reusable Options through Gradient-based Meta Learning
David Kuric, Herke van Hoof
Hierarchical methods in reinforcement learning have the potential to reduce the amount of decisions that the agent needs to perform when learning new tasks. However, finding reusab…
cs.IR2022
Exposure-Aware Recommendation using Contextual 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 is especially problematic when…
cs.AI2022★ 1 cited
Leveraging class abstraction for commonsense reinforcement learning via residual policy gradient methods
Niklas Höpner, Ilaria Tiddi, Herke van Hoof
Enabling reinforcement learning (RL) agents to leverage a knowledge base while learning from experience promises to advance RL in knowledge intensive domains. However, it has prove…