140 citations · 1.3k across the 125 of their papers we have counts for
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Spectral bandits for smooth graph functions with applications in recommender systems
Tomáš Kocák, Michal Valko, Rémi Munos +2
Smooth functions on graphs have wide applications in manifold and semi-supervised learning. In this paper, we study a bandit problem where the payoffs of arms are smooth on a graph…
Spectral bandits
Tomáš Kocák, Rémi Munos, Branislav Kveton +2
Smooth functions on graphs have wide applications in manifold and semi-supervised learning. In this work, we study a bandit problem where the payoffs of arms are smooth on a graph.…
Spectral bandits for smooth graph functions
Michal Valko, Rémi Munos, Branislav Kveton +1
Smooth functions on graphs have wide applications in manifold and semi-supervised learning. In this paper, we study a bandit problem where the payoffs of arms are smooth on a graph…
Uplifting Bandits
Yu-Guan Hsieh, Shiva Prasad Kasiviswanathan, Branislav Kveton
We introduce a multi-armed bandit model where the reward is a sum of multiple random variables, and each action only alters the distributions of some of them. After each action, th…
Conservative Exploration using Interleaving
Sumeet Katariya, Branislav Kveton, Zheng Wen +1
In many practical problems, a learning agent may want to learn the best action in hindsight without ever taking a bad action, which is significantly worse than the default producti…
TopRank: A practical algorithm for online stochastic ranking
Tor Lattimore, Branislav Kveton, Shuai Li +1
Online learning to rank is a sequential decision-making problem where in each round the learning agent chooses a list of items and receives feedback in the form of clicks from the…