Theme Team Metamodeling, Continuous Optimization and Applications (MOCA)
Presentation
The MOCA team studies the management of numerical simulation models and their use in continuous optimization. Metamodeling encompasses here two types of "models of models" :
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Statistical metamodels (e.g., Gaussian processes) that are built from input-output data. The data is often generated by the simulation of physical systems (e.g., with finite elements models). We specialize in statistical metamodels that are compatible with sparse data. Such metamodels typically underly optimization algorithms.
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Metamodels that aim at producing computer programs by describing and processing a class of models. Such metamodels may also be metacodes that algorithmically describe a set of possible program instances.
The team has contributions in domains such as continuous optimization theory and computer experiments. In addition, the group implements simulation softwares for high-performance computing, discrete events simulation and numerical reproductibility.
Keywords:
- Statistical models
- Continuous optimization
- Discrete event simulation
- Scientific Computing
- High Performance Computing
- Numerical reproductibility
News
Last publications
LEARNING FUNCTIONS DEFINED OVER SETS OF VECTORS WITH KERNEL METHODS
5 th ECCOMAS Thematic Conference on Uncertainty Quantification in Computational Sciences and Engineering (UNCECOMP 2023)
Charlie Sire, Didier Rullière, Rodolphe Le Riche, Jérémy Rohmer, Yann Richet, Lucie Pheulpin - April 3, 2023
Augmented quantization : a general approach to mixture models
MASCOT-NUM2023
Marc Grossouvre, Didier Rullière, Jonathan Villot - March 7, 2023
Spatial interpolation using mixture distributions: A Best Linear Unbiased Predictor
Tanguy Appriou - March 6, 2023
Poster on Combination of Kriging models for Bayesian optimization in high-dimension
Marc Grossouvre, Jonathan Villot, Didier Rullière - Jan. 5, 2023
Prédire la performance énergétique des bâtiments
Benoit Albert, Violaine Antoine, Jonas Koko - Jan. 1, 2023
Optimisation de Fuzzy C-Means (FCM) clustering par la méthode des directions alternées (ADMM)
Extraction et Gestion des Connaissances (EGC)
Hassan Maatouk, Didier Rullière, Xavier Bay - Dec. 21, 2022
Large scale Gaussian processes with Matheron's update rule and Karhunen-Loève expansion
Cyrille Mascart, David Hill, Alexandre Muzy, Patricia Reynaud-Bouret - Nov. 22, 2022
Efficient Simulation of Sparse Graphs of Point Processes
ACM Transactions on Modeling and Computer Simulation
Tanguy Appriou - Nov. 17, 2022
Talk on Bayesian optimization for high-dimensional problems
Journées CIROQUO novembre 2022
Mateus Vilela Souza, Bruno Bachelet, Thiago Noronha, Loïc Yon, Christophe Duhamel - Nov. 8, 2022
A Model for Scheduling a Fleet of Autonomous Electric Agricultural Robots
LIV Brazilian Symposium of Operational Research (SBPO)
All publications are here