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20142026
most citedMultivariate Hawkes Processes for Large-scale Inference

9 citations · 25 across the 39 of their papers we have counts for

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5 papers · 1 filter

math.OC2026

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…

math.OC2026

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…

math.OC2024

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…

math.OC2024

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…

math.OC2014★ 2 cited

What Makes a Good Plan? An Efficient Planning Approach to Control Diffusion Processes in Networks

Kevin Scaman, Argyris Kalogeratos, Nicolas Vayatis

In this paper, we analyze the quality of a large class of simple dynamic resource allocation (DRA) strategies which we name priority planning. Their aim is to control an undesired…