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cs.LG2024
Designing an Interpretable Interface for Contextual Bandits
Andrew Maher, Matia Gobbo, Lancelot Lachartre +3
Contextual bandits have become an increasingly popular solution for personalized recommender systems. Despite their growing use, the interpretability of these systems remains a sig…
cs.LG2024
Batched Online Contextual Sparse Bandits with Sequential Inclusion of Features
Rowan Swiers, Subash Prabanantham, Andrew Maher
Multi-armed Bandits (MABs) are increasingly employed in online platforms and e-commerce to optimize decision making for personalized user experiences. In this work, we focus on the…