Safely Exploring Novel Actions in Recommender Systems via Deployment-Efficient Policy Learning

Haruka Kiyohara, Yusuke Narita, Yuta Saito +2

In many real recommender systems, novel items are added frequently over time. The importance of sufficiently presenting novel actions has widely been acknowledged for improving lon…