Christophe Tribes

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Cahiers du GERAD

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NOMAD is software for optimizing blackbox problems. In continuous development since 2001, it constantly evolved with the integration of new algorithmic...

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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 pr...

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We are interested in blackbox optimization for which the user is aware of monotonic behaviour of some constraints defining the problem. That is, when incr...

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The mesh adaptive direct search (MADS) algorithm is designed for blackbox optimization problems for which the functions defining the objective and the constr...

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Despite the lack of theoretical and practical convergence support, the Nelder-Mead (NM) algorithm is widely used to solve unconstrained optimization proble...

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Blackbox optimization problems are often contaminated with numerical noise, and direct search methods such as the Mesh Adaptive Direct Search (MADS) algorit...

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This document describes the NOMAD software, a C++ implementation of the Mesh Adaptive Direct Search (MADS) algorithm designed for constrained optimization of...

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Blackbox optimization deals with situations in which the objective function and constraints are typically computed by launching a time-consuming computer ...

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The Mesh Adaptive Direct Search (MADS) class of algorithms is designed for nonsmooth optimization, where the objective function and constraints are typical...

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