Laurent Meunier

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All published works

Action	Title	Year	Authors
+	On the Role of Randomization in Adversarially Robust Classification	2023	Lucas Gnecco-Heredia Yann Chevaleyre Benjamin Négrevergne Laurent Meunier
+ PDF Chat	On the robustness of randomized classifiers to adversarial examples	2022	Rafaël Pinot Laurent Meunier Florian Yger Cédric Gouy‐Pailler Yann Chevaleyre Jamal Atif
+ PDF Chat	Adversarial Robustness by Design Through Analog Computing And Synthetic Gradients	2022	Alessandro Cappelli Ruben Ohana Julien Launay Laurent Meunier Iacopo Poli Florent Krząkała
+	Towards Consistency in Adversarial Classification	2022	Laurent Meunier Raphaël Ettedgui Rafaël Pinot Yann Chevaleyre Jamal Atif
+	An $\ell^p$-based Kernel Conditional Independence Test	2021	Meyer Scetbon Laurent Meunier Yaniv Romano
+	Scalable Lipschitz Residual Networks with Convex Potential Flows	2021	Laurent Meunier Blaise Delattre Alexandre Araujo Alexandre Allauzen
+ PDF Chat	Black-Box Optimization Revisited: Improving Algorithm Selection Wizards Through Massive Benchmarking	2021	Laurent Meunier Herilalaina Rakotoarison Pak Kan Wong Baptiste Rozière Jérémy Rapin Olivier Teytaud A. Moreau Carola Doerr
+ PDF Chat	Asymptotic convergence rates for averaging strategies	2021	Laurent Meunier Iskander Legheraba Yann Chevaleyre Olivier Teytaud
+ PDF Chat	Adversarial Robustness by Design through Analog Computing and Synthetic Gradients	2021	Alessandro Cappelli Ruben Ohana Julien Launay Laurent Meunier Iacopo Poli Florent Krząkała
+	Mixed Nash Equilibria in the Adversarial Examples Game	2021	Laurent Meunier Meyer Scetbon Rafaël Pinot Jamal Atif Yann Chevaleyre
+	ROPUST: Improving Robustness through Fine-tuning with Photonic Processors and Synthetic Gradients	2021	Alessandro Cappelli Julien Launay Laurent Meunier Ruben Ohana Iacopo Poli
+	An 𝓁 p -based Kernel Conditional Independence Test.	2021	Meyer Scetbon Laurent Meunier Yaniv Romano
+	An Asymptotic Test for Conditional Independence using Analytic Kernel Embeddings	2021	Meyer Scetbon Laurent Meunier Yaniv Romano
+	A Dynamical System Perspective for Lipschitz Neural Networks	2021	Laurent Meunier Blaise Delattre Alexandre Araujo Alexandre Allauzen
+	On the robustness of randomized classifiers to adversarial examples	2021	Rafaël Pinot Laurent Meunier Florian Yger Cédric Gouy‐Pailler Yann Chevaleyre Jamal Atif
+	Black-Box Optimization Revisited: Improving Algorithm Selection Wizards through Massive Benchmarking	2020	Laurent Meunier Herilalaina Rakotoarison Pak Kan Wong Baptiste Rozière Jérémy Rapin Olivier Teytaud A. Moreau Carola Doerr
+	Handling Multiple Costs in Optimal Transport: Strong Duality and Efficient Computation.	2020	Meyer Scetbon Laurent Meunier Jamal Atif Marco Cuturi
+	Variance Reduction for Better Sampling in Continuous Domains	2020	Laurent Meunier Carola Doerr Jérémy Rapin Olivier Teytaud
+	Proving $\mu>1$	2020	Laurent Meunier Yann Chevaleyre Jérémy Rapin Clément W. Royer Olivier Teytaud
+	On averaging the best samples in evolutionary computation	2020	Laurent Meunier Yann Chevaleyre Jérémy Rapin Clément W. Royer Olivier Teytaud
+	Adversarial Attacks on Linear Contextual Bandits	2020	Evrard Garcelon Baptiste Rozière Laurent Meunier Jean Tarbouriech Olivier Teytaud Alessandro Lazaric Matteo Pirotta
+ PDF Chat	On Averaging the Best Samples in Evolutionary Computation	2020	Laurent Meunier Yann Chevaleyre Jérémy Rapin Clément W. Royer Olivier Teytaud
+ PDF Chat	Variance Reduction for Better Sampling in Continuous Domains	2020	Laurent Meunier Carola Doerr Jérémy Rapin Olivier Teytaud
+	Equitable and Optimal Transport with Multiple Agents	2020	Meyer Scetbon Laurent Meunier Jamal Atif Marco Cuturi
+ PDF Chat	Advocating for Multiple Defense Strategies Against Adversarial Examples	2020	Alexandre Araujo Laurent Meunier Rafaël Pinot Benjamin Négrevergne
+	Variance Reduction for Better Sampling in Continuous Domains	2020	Laurent Meunier Carola Doerr Jérémy Rapin Olivier Teytaud
+	On averaging the best samples in evolutionary computation	2020	Laurent Meunier Yann Chevaleyre Jérémy Rapin Clément W. Royer Olivier Teytaud
+	Black-Box Optimization Revisited: Improving Algorithm Selection Wizards through Massive Benchmarking	2020	Laurent Meunier Herilalaina Rakotoarison Pak Kan Wong Baptiste Rozière Jérémy Rapin Olivier Teytaud A. Moreau Carola Doerr
+	Yet another but more efficient black-box adversarial attack: tiling and evolution strategies	2019	Laurent Meunier Jamal Atif Olivier Teytaud
+	Theoretical evidence for adversarial robustness through randomization: the case of the Exponential family.	2019	Rafaël Pinot Laurent Meunier Alexandre Araujo Hisashi Kashima Florian Yger Cédric Gouy‐Pailler Jamal Atif
+	Robust Neural Networks using Randomized Adversarial Training	2019	Alexandre Araujo Rafaël Pinot Benjamin Négrevergne Laurent Meunier Yann Chevaleyre Florian Yger Jamal Atif
+	Theoretical evidence for adversarial robustness through randomization	2019	Rafaël Pinot Laurent Meunier Alexandre Araujo Hisashi Kashima Florian Yger Cédric Gouy‐Pailler Jamal Atif
+	Yet another but more efficient black-box adversarial attack: tiling and evolution strategies	2019	Laurent Meunier Jamal Atif Olivier Teytaud

Common Coauthors

Coauthor	Papers Together
Olivier Teytaud	14
Yann Chevaleyre	11
Jamal Atif	11
Jérémy Rapin	10
Rafaël Pinot	8
Alexandre Araujo	6
Meyer Scetbon	6
Carola Doerr	6
Florian Yger	5
Baptiste Rozière	4
Clément W. Royer	4
Cédric Gouy‐Pailler	4
A. Moreau	3
Ruben Ohana	3
Yaniv Romano	3
Herilalaina Rakotoarison	3
Iacopo Poli	3
Benjamin Négrevergne	3
Pak Kan Wong	3
Blaise Delattre	2
Alexandre Allauzen	2
Marco Cuturi	2
Alessandro Cappelli	2
Hisashi Kashima	2
Florent Krza̧kała	2
Julien Launay	2
Alessandro Lazaric	1
Jean Tarbouriech	1
Alessandro Cappelli	1
Iskander Legheraba	1
Evrard Garcelon	1
Raphaël Ettedgui	1
Matteo Pirotta	1
Lucas Gnecco-Heredia	1
Julien Launay	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+	Towards Deep Learning Models Resistant to Adversarial Attacks.	2018	Aleksander Mądry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu	7
+	Adversarial examples in the physical world	2016	Alexey Kurakin Ian Goodfellow Samy Bengio	7
+ PDF Chat	Certified Robustness to Adversarial Examples with Differential Privacy	2019	Mathias Lécuyer Vaggelis Atlidakis Roxana Geambasu Daniel Hsu Suman Jana	6
+ PDF Chat	Towards Evaluating the Robustness of Neural Networks	2017	Nicholas Carlini David Wagner	5
+ PDF Chat	Deep Residual Learning for Image Recognition	2016	Kaiming He Xiangyu Zhang Shaoqing Ren Jian Sun	5
+ PDF Chat	Pure Exploration in Multi-armed Bandits Problems	2009	Sébastien Bubeck Rémi Munos Gilles Stoltz	4
+	Evasion Attacks against Machine Learning at Test Time	2013	Battista Biggio Igino Corona Davide Maiorca Blaine Nelson Nedim Šrndić Pavel Laskov Giorgio Giacinto Fabio Roli	4
+ PDF Chat	Variance Reduction for Better Sampling in Continuous Domains	2020	Laurent Meunier Carola Doerr Jérémy Rapin Olivier Teytaud	4
+	Critical Hyper-Parameters: No Random, No Cry	2017	Olivier Bousquet Sylvain Gelly Karol Kurach Olivier Teytaud Damien Vincent	4
+	None	1997	Rainer Storn Kenneth V. Price	4
+ PDF Chat	The Limitations of Deep Learning in Adversarial Settings	2016	Nicolas Papernot Patrick McDaniel Somesh Jha Matt Fredrikson Z. Berkay Celik Ananthram Swami	4
+	Wide Residual Networks	2016	Sergey Zagoruyko Nikos Komodakis	4
+	Mitigating Adversarial Effects Through Randomization	2017	Cihang Xie Jianyu Wang Zhishuai Zhang Zhou Ren Alan Yuille	4
+	Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples	2018	Anish Athalye Nicholas Carlini David T. Wagner	4
+ PDF Chat	EAD: Elastic-Net Attacks to Deep Neural Networks via Adversarial Examples	2018	Pin‐Yu Chen Yash Sharma Huan Zhang Jinfeng Yi Cho‐Jui Hsieh	3
+ PDF Chat	Parametric Noise Injection: Trainable Randomness to Improve Deep Neural Network Robustness Against Adversarial Attack	2019	Zhezhi He Adnan Siraj Rakin Deliang Fan	3
+	Theoretical evidence for adversarial robustness through randomization	2019	Rafaël Pinot Laurent Meunier Alexandre Araujo Hisashi Kashima Florian Yger Cédric Gouy‐Pailler Jamal Atif	3
+	Certified Adversarial Robustness via Randomized Smoothing	2019	Jeremy M. Cohen Elan Rosenfeld J. Zico Kolter	3
+	Random Number Generation and Quasi-Monte Carlo Methods.	1993	Bruce Jay Collings Harald Niederreiter	3
+ PDF Chat	Towards Robust Neural Networks via Random Self-ensemble	2018	Xuanqing Liu Minhao Cheng Huan Zhang Cho‐Jui Hsieh	3
+	Certifying Some Distributional Robustness with Principled Adversarial Training	2017	Aman Sinha Hongseok Namkoong Riccardo Volpi John C. Duchi	3
+ PDF Chat	Why one must use reweighting in estimation of distribution algorithms	2009	Fabien Teytaud Olivier Teytaud	3
+	Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples	2018	Anish Athalye Nicholas Carlini David Wagner	3
+	Explaining and Harnessing Adversarial Examples	2014	Ian Goodfellow Jonathon Shlens Christian Szegedy	3
+ PDF Chat	Topics in Optimal Transportation	2003	Cédric Villani	3
+	Provably Robust Deep Learning via Adversarially Trained Smoothed Classifiers	2019	Hadi Salman Vassilia Michailidis Ilya Razenshteyn Pengchuan Zhang Huan Zhang Sébastien Bubeck Greg Yang	3
+	On Evaluating Adversarial Robustness	2019	Nicholas Carlini Anish Athalye Nicolas Papernot Wieland Brendel Jonas Rauber Dimitris Tsipras Ian Goodfellow Aleksander Mądry Alexey Kurakin	3
+	Wide Residual Networks	2016	Sergey Zagoruyko Nikos Komodakis	3
+	On Choosing and Bounding Probability Metrics	2002	Alison L. Gibbs Francis Edward Su	2
+	Robustness of classifiers: from adversarial to random noise	2016	Alhussein Fawzi Seyed-Mohsen Moosavi-Dezfooli Pascal Frossard	2
+	Very Deep Convolutional Networks for Large-Scale Image Recognition	2014	Karen Simonyan Andrew Zisserman	2
+	On the efficiency of certain quasi-random sequences of points in evaluating multi-dimensional integrals	1960	John H. Halton	2
+	On the Non-asymptotic and Sharp Lower Tail Bounds of Random Variables	2018	Anru R. Zhang Yuchen Zhou	2
+	Automated Algorithm Selection: Survey and Perspectives	2018	Pascal Kerschke Holger H. Hoos Frank Neumann Heike Trautmann	2
+	Theoretical evidence for adversarial robustness through randomization: the case of the Exponential family.	2019	Rafaël Pinot Laurent Meunier Alexandre Araujo Hisashi Kashima Florian Yger Cédric Gouy‐Pailler Jamal Atif	2
+	Parsimonious Black-Box Adversarial Attacks via Efficient Combinatorial Optimization	2019	Seungyong Moon Gaon An Hyun Oh Song	2
+ PDF Chat	SATzilla: Portfolio-based Algorithm Selection for SAT	2008	Lizhong Xu Frank Hutter Holger H. Hoos Kevin Leyton‐Brown	2
+ PDF Chat	ZOO	2017	Pin‐Yu Chen Huan Zhang Yash Sharma Jinfeng Yi Cho‐Jui Hsieh	2
+	Stochastic Activation Pruning for Robust Adversarial Defense	2018	Guneet S. Dhillon Kamyar Azizzadenesheli Zachary C. Lipton Jeremy Bernstein Jean Kossaifi Aran Khanna Anima Anandkumar	2
+	Center-point-based Simulated Annealing	2012	Ali Esmailzadeh Shahryar Rahnamayan	2
+	An efficient method for finding the minimum of a function of several variables without calculating derivatives	1964	M. J. D. Powell	2
+ PDF Chat	On Pinsker's and Vajda's Type Inequalities for Csiszár's $f$-Divergences	2010	Gustavo L. Gilardoni	2
+ PDF Chat	Universal Adversarial Perturbations	2017	Seyed-Mohsen Moosavi-Dezfooli Alhussein Fawzi Omar Fawzi Pascal Frossard	2
+	Synthesizing Robust Adversarial Examples	2017	Anish Athalye Logan Engstrom Andrew Ilyas Kevin Kwok	2
+	Black-box Adversarial Attacks with Limited Queries and Information.	2018	Andrew Ilyas Logan Engstrom Anish Athalye Jessy Lin	2
+	The Effectiveness of Data Augmentation in Image Classification using Deep Learning	2017	Luis Perez Jason Wang	2
+	A computationally efficient limited memory CMA-ES for large scale optimization	2014	Ilya Loshchilov	2
+	Scikit-learn: Machine Learning in Python	2012	Fabián Pedregosa Gaël Varoquaux Alexandre Gramfort Vincent Michel Bertrand Thirion Olivier Grisel Mathieu Blondel Peter Prettenhofer Ron J. Weiss Vincent Dubourg	2
+	A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems	2009	Amir Beck Marc Teboulle	2
+	Transferability in Machine Learning: from Phenomena to Black-Box Attacks using Adversarial Samples	2016	Nicolas Papernot Patrick McDaniel Ian Goodfellow	2