140 citations · 438 across the 8 of their papers we have counts for
6 papers · 1 filter
Combinatorial Cascading Bandits
Branislav Kveton, Zheng Wen, Azin Ashkan +1
We propose combinatorial cascading bandits, a class of partial monitoring problems where at each step a learning agent chooses a tuple of ground items subject to constraints and re…
Cascading Bandits: Learning to Rank in the Cascade Model
Branislav Kveton, Csaba Szepesvari, Zheng Wen +1
A search engine usually outputs a list of web pages. The user examines this list, from the first web page to the last, and chooses the first attractive page. This model of user…
Tight Regret Bounds for Stochastic Combinatorial Semi-Bandits
Branislav Kveton, Zheng Wen, Azin Ashkan +1
A stochastic combinatorial semi-bandit is an online learning problem where at each step a learning agent chooses a subset of ground items subject to constraints, and then observes…
Efficient Learning in Large-Scale Combinatorial Semi-Bandits
Zheng Wen, Branislav Kveton, Azin Ashkan
A stochastic combinatorial semi-bandit is an online learning problem where at each step a learning agent chooses a subset of ground items subject to combinatorial constraints, and…
Learning to Act Greedily: Polymatroid Semi-Bandits
Branislav Kveton, Zheng Wen, Azin Ashkan +1
Many important optimization problems, such as the minimum spanning tree and minimum-cost flow, can be solved optimally by a greedy method. In this work, we study a learning variant…
Matroid Bandits: Fast Combinatorial Optimization with Learning
Branislav Kveton, Zheng Wen, Azin Ashkan +2
A matroid is a notion of independence in combinatorial optimization which is closely related to computational efficiency. In particular, it is well known that the maximum of a cons…