Publications

Conference papers

Asymptotic convergence rates for averaging strategies
Laurent Meunier, Iskander Legheraba, Yann Chevaleyre and Olivier Teytaud
Foundations Of Genetic Algorithms (FOGA 2021).

paper

Mixed Nash Equilibria in the Adversarial Examples Game
Laurent Meunier^*, Meyer Scetbon^*, Rafael Pinot, Jamal Atif, Yann Chevaleyre
International Conference on Machine Learning (ICML 2021).
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Equitable and Optimal Transport with Multiple Agents
Meyer Scetbon^*, Laurent Meunier^*, Jamal Atif, Marco Cuturi
Artificial Intelligence and Statistics (AISTATS 2021).
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Adversarial Attacks on Linear Contextual Bandits
Evrard Garcelon^*, Baptiste Roziere^*, Laurent Meunier^*, Jean Tarbouriech, Olivier Teytaud, Alessandro Lazaric, Matteo Pirotta
Advances in Neural Information Processing Systems (NeurIPS 2020).
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Variance Reduction for Better Sampling in Continuous Domains
Laurent Meunier, Carola Doerr, Jeremy Rapin, Olivier Teytaud
International Conference on Parallel Problem Solving from Nature (PPSN 2020).
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On averaging the best samples in evolutionary computation
Laurent Meunier, Yann Chevaleyre, Jeremy Rapin, Clément W Royer, Olivier Teytaud
International Conference on Parallel Problem Solving from Nature (PPSN 2020).
Best paper nominee. paper

Theoretical evidence for adversarial robustness through randomization
Rafael Pinot, Laurent Meunier, Alexandre Araujo, Hisashi Kashima, Florian Yger, Cédric Gouy-Pailler, Jamal Atif
Advances in Neural Information Processing Systems (NeurIPS 2019).
paper

Journal papers

Black-Box Optimization Revisited: Improving Algorithm Selection Wizards through Massive Benchmarking
Laurent Meunier, Herilalaina Rakotoarison, Pak Kan Wong, Baptiste Roziere, Jeremy Rapin, Olivier Teytaud, Antoine Moreau, Carola Doerr
IEEE Transactions on Evolutionary Computation (2021)
paper

Workshop papers

ROPUST: Improving Robustness through Fine-tuning with Photonic Processors and Synthetic Gradients
Alessandro Cappelli, Ruben Ohana, Julien Launay, Laurent Meunier, Iacopo Poli
Workshop on Adversarial Machine Learning (ICML 2021)
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Advocating for Multiple Defense Strategies against Adversarial Examples
Alexandre Araujo, Laurent Meunier, Rafael Pinot, Benjamin Negrevergne
Workshop on Machine Learning for CyberSecurity (MLCS@ECML-PKDD 2020)
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Under review and preprint papers

On the robustness of randomized classifiers to adversarial examples
Rafael Pinot^*, Laurent Meunier^*, Florian Yger, Cédric Gouy-Pailler, Yann Chevaleyre, Jamal Atif
paper

Yet another but more efficient black-box adversarial attack: tiling and evolution strategies
Laurent Meunier, Jamal Atif, Olivier Teytaud
paper