5 citations · 5 across the 4 of their papers we have counts for
4 papers
UniRank: Unimodal Bandit Algorithm for Online Ranking
Camille-Sovanneary Gauthier, Romaric Gaudel, Elisa Fromont
We tackle a new emerging problem, which is finding an optimal monopartite matching in a weighted graph. The semi-bandit version, where a full matching is sampled at each iteration,…
Unimodal Mono-Partite Matching in a Bandit Setting
Romaric Gaudel, Matthieu Rodet
We tackle a new emerging problem, which is finding an optimal monopartite matching in a weighted graph. The semi-bandit version, where a full matching is sampled at each iteration,…
s-LIME: Reconciling Locality and Fidelity in Linear Explanations
Romaric Gaudel, Luis Galárraga, Julien Delaunay +2
The benefit of locality is one of the major premises of LIME, one of the most prominent methods to explain black-box machine learning models. This emphasis relies on the postulate…
Bandits Warm-up Cold Recommender Systems
Jérémie Mary, Romaric Gaudel, Preux Philippe
We address the cold start problem in recommendation systems assuming no contextual information is available neither about users, nor items. We consider the case in which we only ha…