2 citations · 2 across the 6 of their papers we have counts for
6 papers
GLOBe: A Modular Global Optimization library
Gaëtan Serré, Argyris Kalogeratos, Nicolas Vayatis
Open-source libraries are have a catalytic role in research pipelines, where new methods must be compared against up-to-date baselines. We present the GLobal Optimization Benchmark…
Enhancing Exploration in Global Optimization by Noise Injection in the Probability Measures Space
Gaëtan Serré, Pierre Germain, Samuel Gruffaz +1
McKean-Vlasov (MKV) systems provide a unifying framework for recent state-of-the-art particlebased methods for global optimization. While individual particles follow stochastic tra…
A Unifying Framework for Global Optimization: From Theory to Formalization
Gaëtan Serré, Argyris Kalogeratos, Nicolas Vayatis
We introduce an abstract measure___theoretic framework that serves as a tool to rigorously study stochastic iterative global optimization algorithms as a unified class. The framewo…
LIPO+: Frugal Global Optimization for Lipschitz Functions
Gaëtan Serré, Perceval Beja-Battais, Sophia Chirrane +2
In this paper, we propose simple yet effective empirical improvements to the algorithms of the LIPO family, introduced in [Malherbe2017], that we call LIPO+ and AdaLIPO+. We compar…
Stein Boltzmann Sampling: A Variational Approach for Global Optimization
Gaëtan Serré, Argyris Kalogeratos, Nicolas Vayatis
In this paper, we present a flow-based method for global optimization of continuous Sobolev functions, called Stein Boltzmann Sampling (SBS). SBS initializes uniformly a number of…
Reinforcement learning for Energies of the future and carbon neutrality: a Challenge Design
Gaëtan Serré, Eva Boguslawski, Benjamin Donnot +3
Current rapid changes in climate increase the urgency to change energy production and consumption management, to reduce carbon and other green-house gas production. In this context…