5 citations · 10 across the 21 of their papers we have counts for
6 papers · 1 filter
Constant regret in general games via higher-order optimism
Omar Abbadi, Rida Laraki, Panayotis Mertikopoulos
We introduce an uncoupled learning algorithm which, when employed by all players of an arbitrary -player normal form game with up to actions per player, guarantees $O(N^3\lo…
An -No-Regret Algorithm For Graphical Bilinear Bandits
Geovani Rizk, Igor Colin, Albert Thomas +2
We propose the first regret-based approach to the Graphical Bilinear Bandits problem, where agents in a graph play a stochastic bilinear bandit game with each of their neighbor…
Best Arm Identification in Graphical Bilinear Bandits
Geovani Rizk, Albert Thomas, Igor Colin +2
We introduce a new graphical bilinear bandit problem where a learner (or a \emph{central entity}) allocates arms to the nodes of a graph and observes for each edge a noisy bilinear…
NGO-GM: Natural Gradient Optimization for Graphical Models
Eric Benhamou, Jamal Atif, Rida Laraki +1
This paper deals with estimating model parameters in graphical models. We reformulate it as an information geometric optimization problem and introduce a natural gradient descent s…
A discrete version of CMA-ES
Eric Benhamou, Jamal Atif, Rida Laraki
Modern machine learning uses more and more advanced optimization techniques to find optimal hyper parameters. Whenever the objective function is non-convex, non continuous and with…
A new approach to learning in Dynamic Bayesian Networks (DBNs)
E. Benhamou, J. Atif, R. Laraki
In this paper, we revisit the parameter learning problem, namely the estimation of model parameters for Dynamic Bayesian Networks (DBNs). DBNs are directed graphical models of stoc…