56 citations · 200 across the 32 of their papers we have counts for
3 papers · 1 filter
Stochastic Rank-1 Bandits
Sumeet Katariya, Branislav Kveton, Csaba Szepesvari +2
We propose stochastic rank- bandits, a class of online learning problems where at each step a learning agent chooses a pair of row and column arms, and receives the product of t…
Multiple-Play Bandits in the Position-Based Model
Paul Lagrée, Claire Vernade, Olivier Cappé
Sequentially learning to place items in multi-position displays or lists is a task that can be cast into the multiple-play semi-bandit setting. However, a major concern in this con…
Sequential ranking under random semi-bandit feedback
Hossein Vahabi, Paul Lagrée, Claire Vernade +1
In many web applications, a recommendation is not a single item suggested to a user but a list of possibly interesting contents that may be ranked in some contexts. The combinatori…