30 citations · 69 across the 12 of their papers we have counts for
5 papers · 1 filter
Impatient Bandits: Optimizing Recommendations for the Long-Term Without Delay
Thomas M. McDonald, Lucas Maystre, Mounia Lalmas +2
Recommender systems are a ubiquitous feature of online platforms. Increasingly, they are explicitly tasked with increasing users' long-term satisfaction. In this context, we study…
Fast Interactive Search with a Scale-Free Comparison Oracle
Daniyar Chumbalov, Lars Klein, Lucas Maystre +1
A comparison-based search algorithm lets a user find a target item in a database by answering queries of the form, ``Which of items and is closer to ?'' Instead of f…
Estimating long-term causal effects from short-term experiments and long-term observational data with unobserved confounding
Graham Van Goffrier, Lucas Maystre, Ciarán Gilligan-Lee
Understanding and quantifying cause and effect is an important problem in many domains. The generally-agreed solution to this problem is to perform a randomised controlled trial. H…
A Strong Baseline for Batch Imitation Learning
Matthew Smith, Lucas Maystre, Zhenwen Dai +1
Imitation of expert behaviour is a highly desirable and safe approach to the problem of sequential decision making. We provide an easy-to-implement, novel algorithm for imitation l…
Optimizing Audio Recommendations for the Long-Term: A Reinforcement Learning Perspective
Lucas Maystre, Daniel Russo, Yu Zhao
We present a novel podcast recommender system deployed at industrial scale. This system successfully optimizes personal listening journeys that unfold over months for hundreds of m…