Title :

COCO: The Experimental Procedure

Author(s) :

Hansen, Nikolaus [Auteur]
Machine Learning and Optimisation [TAO]
Tušar, Tea [Auteur]
Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Mersmann, Olaf [Auteur]
Technische Universität Dortmund [Dortmund] [TU]
Auger, Anne [Auteur]
Machine Learning and Optimisation [TAO]
Brockhoff, Dimo [Auteur]
Parallel Cooperative Multi-criteria Optimization [DOLPHIN]

English keyword(s) :

Black-box
Optimization
Numerical optimization
Benchmarking

HAL domain(s) :

Informatique [cs]/Réseau de neurones [cs.NE]
Informatique [cs]/Analyse numérique [cs.NA]
Informatique [cs]/Performance et fiabilité [cs.PF]
Informatique [cs]/Logiciel mathématique [cs.MS]
Informatique [cs]/Apprentissage [cs.LG]

English abstract : [en]

We present a budget-free experimental setup and procedure for benchmarking numericaloptimization algorithms in a black-box scenario. This procedure can be applied with the COCO benchmarking platform. We describe initialization ...
Show more >We present a budget-free experimental setup and procedure for benchmarking numericaloptimization algorithms in a black-box scenario. This procedure can be applied with the COCO benchmarking platform. We describe initialization of and input to the algorithm and touch upon therelevance of termination and restarts.Show less >

Language :

Anglais

ANR Project :

Analyse, Amelioration, Evaluation d'algorithmes numériques pour l'optimisation boîte-noire

Comment :

ArXiv e-prints, arXiv:1603.08776

Collections :

• Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL