129 citations · 210 across the 8 of their papers we have counts for
5 papers · 1 filter
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.…
Online learning with Erdős-Rényi side-observation graphs
Tomáš Kocák, Gergely Neu, Michal Valko
We consider adversarial multi-armed bandit problems where the learner is allowed to observe losses of a number of arms beside the arm that it actually chose. We study the case wher…
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…
On the complexity of All -Best Arms Identification
Aymen Al Marjani, Tomáš Kocák, Aurélien Garivier
We consider the question introduced by \cite{Mason2020} of identifying all the -optimal arms in a finite stochastic multi-armed bandit with Gaussian rewards. We give t…