activity
20052022
most citedOn the Complexity of Best Arm Identification in Multi-Armed Bandit Models

688 citations · 2.3k across the 21 of their papers we have counts for

collaborators

22 papers

cs.AI2022

Stochastic Direct Search Method for Blind Resource Allocation

Juliette Achddou, Olivier Cappe, Aurélien Garivier

Motivated by programmatic advertising optimization, we consider the task of sequentially allocating budget across a set of resources. At every time step, a feasible allocation is c…

stat.ML2020★ 2 cited

A Comparative Study of Gamma Markov Chains for Temporal Non-Negative Matrix Factorization

Louis Filstroff, Olivier Gouvert, Cédric Févotte +1

Non-negative matrix factorization (NMF) has become a well-established class of methods for the analysis of non-negative data. In particular, a lot of effort has been devoted to pro…

cs.LG2019★ 56 cited

Weighted Linear Bandits for Non-Stationary Environments

Yoan Russac, Claire Vernade, Olivier Cappé

We consider a stochastic linear bandit model in which the available actions correspond to arbitrary context vectors whose associated rewards follow a non-stationary linear regressi…

cs.LG2017★ 27 cited

Stochastic Bandit Models for Delayed Conversions

Claire Vernade, Olivier Cappé, Vianney Perchet

Online advertising and product recommendation are important domains of applications for multi-armed bandit methods. In these fields, the reward that is immediately available is mos…

cs.SI2017

Algorithms for Online Influencer Marketing

Paul Lagrée, Olivier Cappé, Bogdan Cautis +1

Influence maximization is the problem of finding influential users, or nodes, in a graph so as to maximize the spread of information. It has many applications in advertising and ma…

cs.LG2016★ 24 cited

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…