17 citations · 38 across the 8 of their papers we have counts for
4 papers · 1 filter
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…
Cumulative Step-size Adaptation on Linear Functions
Alexandre Chotard, Anne Auger, Nikolaus Hansen
The CSA-ES is an Evolution Strategy with Cumulative Step size Adaptation, where the step size is adapted measuring the length of a so-called cumulative path. The cumulative path is…
Cumulative Step-size Adaptation on Linear Functions: Technical Report
Alexandre Adrien Chotard, Anne Auger, Nikolaus Hansen
The CSA-ES is an Evolution Strategy with Cumulative Step size Adaptation, where the step size is adapted measuring the length of a so-called cumulative path. The cumulative path is…