Dilina Rajapakse and Douglas Leith, "Fast And Accurate User Cold-Start Learning Using Monte Carlo Tree Search", Proc RecSys, September 2022
Recommender systems need to quickly learn the preferences of new users. In this work, SCSS researchers use an approach inspired by single-player games to learn preferences more quickly and more accurately than the state-of-the-art, consistently beating previous methods across all datasets studied.