no code implementations • 25 Jan 2017 • Shi Zong, Branislav Kveton, Shlomo Berkovsky, Azin Ashkan, Nikos Vlassis, Zheng Wen
To the best of our knowledge, this is the first large-scale causal study of the impact of weather on TV watching patterns.
no code implementations • NeurIPS 2015 • Branislav Kveton, Zheng Wen, Azin Ashkan, Csaba Szepesvari
The agent observes the index of the first chosen item whose weight is zero.
no code implementations • 10 Feb 2015 • Branislav Kveton, Csaba Szepesvari, Zheng Wen, Azin Ashkan
We also prove gap-dependent upper bounds on the regret of these algorithms and derive a lower bound on the regret in cascading bandits.
no code implementations • 13 Nov 2014 • Azin Ashkan, Branislav Kveton, Shlomo Berkovsky, Zheng Wen
The need for diversification of recommendation lists manifests in a number of recommender systems use cases.
no code implementations • 3 Oct 2014 • Branislav Kveton, Zheng Wen, Azin Ashkan, Csaba Szepesvari
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 stochastic weights of these items and receives their sum as a payoff.
no code implementations • 28 Jun 2014 • 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 then observes stochastic weights of these items and receives their sum as a payoff.
no code implementations • 30 May 2014 • Branislav Kveton, Zheng Wen, Azin Ashkan, Michal Valko
Many important optimization problems, such as the minimum spanning tree and minimum-cost flow, can be solved optimally by a greedy method.
no code implementations • 20 Mar 2014 • Branislav Kveton, Zheng Wen, Azin Ashkan, Hoda Eydgahi, Brian Eriksson
The objective in these problems is to learn how to maximize a modular function on a matroid.