1k citations
- Stanford UniversityUS33 papers
- Google (United States)US32 papers
- University of Illinois Urbana-ChampaignUS32 papers
- University of California, BerkeleyUS29 papers
- Massachusetts Institute of TechnologyUS28 papers
- Carnegie Mellon UniversityUS26 papers
- University of California San DiegoUS25 papers
- University College LondonGB22 papers
- Georgia Institute of TechnologyUS21 papers
- University of Maryland, College ParkUS21 papers
- University of MichiganUS18 papers
- University of Southern CaliforniaUS16 papers
Showing 2014 · cs.LGShow all
2 papers · 2 filters
cs.LG2014★ 140 cited
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…
cs.LG2014★ 47 cited
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…