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32 papers · 1 filter
A hierarchical Bayesian perspective on majorization-minimization for non-convex sparse regression: application to M/EEG source imaging
Yousra Bekhti, Felix Lucka, Joseph Salmon +1
Majorization-minimization (MM) is a standard iterative optimization technique which consists in minimizing a sequence of convex surrogate functionals. MM approaches have been parti…
Adaptive restart of accelerated gradient methods under local quadratic growth condition
Olivier Fercoq, Zheng Qu
By analyzing accelerated proximal gradient methods under a local quadratic growth condition, we show that restarting these algorithms at any frequency gives a globally linearly con…
Connecting Width and Structure in Knowledge Compilation (Extended Version)
Antoine Amarilli, Mikaël Monet, Pierre Senellart
Several query evaluation tasks can be done via knowledge compilation: the query result is compiled as a lineage circuit from which the answer can be determined. For such tasks, it…
Exact and Approximate Algorithms for Computing Betweenness Centrality in Directed Graphs
Mostafa Haghir Chehreghani, Albert Bifet, Talel Abdessalem
Graphs (networks) are an important tool to model data in different domains. Real-world graphs are usually directed, where the edges have a direction and they are not symmetric. Bet…
Max K-armed bandit: On the ExtremeHunter algorithm and beyond
Mastane Achab, Stephan Clémençon, Aurélien Garivier +2
This paper is devoted to the study of the max K-armed bandit problem, which consists in sequentially allocating resources in order to detect extreme values. Our contribution is two…
Stochastic Bandit Models for Delayed Conversions
Claire Vernade, Olivier Cappé, Vianney Perchet
Online advertising and product recommendation are important domains of applications for multi-armed bandit methods. In these fields, the reward that is immediately available is mos…