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9 papers · 1 filter
Black-box optimization of noisy functions with unknown smoothness
Jean-Bastien Grill, Michal Valko, Rémi Munos
We study the problem of black-box optimization of a function f of any dimension, given function evaluations perturbed by noise. The function is assumed to be locally smooth around…
Active multiple matrix completion with adaptive confidence sets
Andrea Locatelli, Alexandra Carpentier, Michal Valko
In this work, we formulate a new multi-task active learning setting in which the learner's goal is to solve multiple matrix completion problems simultaneously. At each round, the l…
A single algorithm for both restless and rested rotting bandits
Julien Seznec, Pierre Ménard, Alessandro Lazaric +1
In many application domains (e.g., recommender systems, intelligent tutoring systems), the rewards associated to the actions tend to decrease over time. This decay is either caused…
On two ways to use determinantal point processes for Monte Carlo integration
Guillaume Gautier, Rémi Bardenet, Michal Valko
The standard Monte Carlo estimator of relies on independent samples from and has variance of order . Replacing the samples with a…
Planning in entropy-regularized Markov decision processes and games
Jean-Bastien Grill, Omar Darwiche Domingues, Pierre Ménard +2
We propose SmoothCruiser, a new planning algorithm for estimating the value function in entropy-regularized Markov decision processes and two-player games, given a generative model…
Budgeted Online Influence Maximization
Pierre Perrault, Jennifer Healey, Zheng Wen +1
We introduce a new budgeted framework for online influence maximization, considering the total cost of an advertising campaign instead of the common cardinality constraint on a cho…