160 citations · 1.2k across the 55 of their papers we have counts for
4 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…
Online Influence Maximization under Independent Cascade Model with Semi-Bandit Feedback
Zheng Wen, Branislav Kveton, Michal Valko +1
We study the online influence maximization problem in social networks under the independent cascade model. Specifically, we aim to learn the set of "best influencers" in a social n…
Cascading Bandits for Large-Scale Recommendation Problems
Shi Zong, Hao Ni, Kenny Sung +3
Most recommender systems recommend a list of items. The user examines the list, from the first item to the last, and often chooses the first attractive item and does not examine th…
DCM Bandits: Learning to Rank with Multiple Clicks
Sumeet Katariya, Branislav Kveton, Csaba Szepesvári +1
A search engine recommends to the user a list of web pages. The user examines this list, from the first page to the last, and clicks on all attractive pages until the user is satis…