46 citations · 63 across the 6 of their papers we have counts for
8 papers
Handling of constraints in multiobjective blackbox optimization
Jean Bigeon, Sébastien Le Digabel, Ludovic Salomon
This work proposes the integration of two new constraint-handling approaches into the blackbox constrained multiobjective optimization algorithm DMulti-MADS, an extension of the Me…
NOMAD version 4: Nonlinear optimization with the MADS algorithm
Charles Audet, Sébastien Le Digabel, Viviane Rochon Montplaisir +1
NOMAD is software for optimizing blackbox problems. In continuous development since 2001, it constantly evolved with the integration of new algorithmic features published in scient…
Tuning a variational autoencoder for data accountability problem in the Mars Science Laboratory ground data system
Dounia Lakhmiri, Ryan Alimo, Sebastien Le Digabel
The Mars Curiosity rover is frequently sending back engineering and science data that goes through a pipeline of systems before reaching its final destination at the mission operat…
Optimization of noisy blackboxes with adaptive precision
Stéphane Alarie, Charles Audet, Pierre-Yves Bouchet +1
In derivative-free and blackbox optimization, the objective function is often evaluated through the execution of a computer program seen as a blackbox. It can be noisy, in the sens…
StoMADS: Stochastic blackbox optimization using probabilistic estimates
Charles Audet, Kwassi Joseph Dzahini, Michael Kokkolaras +1
This work introduces StoMADS, a stochastic variant of the mesh adaptive direct-search (MADS) algorithm originally developed for deterministic blackbox optimization. StoMADS conside…
HyperNOMAD: Hyperparameter optimization of deep neural networks using mesh adaptive direct search
Dounia Lakhmiri, Sébastien Le Digabel, Christophe Tribes
The performance of deep neural networks is highly sensitive to the choice of the hyperparameters that define the structure of the network and the learning process. When facing a ne…