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Nicolas Flammarion

LIENS, SIERRA

RobustBench: a standardized adversarial robustness benchmark

Oct 19, 2020
Francesco Croce, Maksym Andriushchenko, Vikash Sehwag, Nicolas Flammarion, Mung Chiang, Prateek Mittal, Matthias Hein


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Optimal Robust Linear Regression in Nearly Linear Time

Jul 16, 2020
Yeshwanth Cherapanamjeri, Efe Aras, Nilesh Tripuraneni, Michael I. Jordan, Nicolas Flammarion, Peter L. Bartlett


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Understanding and Improving Fast Adversarial Training

Jul 06, 2020
Maksym Andriushchenko, Nicolas Flammarion


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On Convergence-Diagnostic based Step Sizes for Stochastic Gradient Descent

Jul 01, 2020
Scott Pesme, Aymeric Dieuleveut, Nicolas Flammarion


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Online Robust Regression via SGD on the l1 loss

Jul 01, 2020
Scott Pesme, Nicolas Flammarion


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Sparse-RS: a versatile framework for query-efficient sparse black-box adversarial attacks

Jun 23, 2020
Francesco Croce, Maksym Andriushchenko, Naman D. Singh, Nicolas Flammarion, Matthias Hein


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Square Attack: a query-efficient black-box adversarial attack via random search

Nov 29, 2019
Maksym Andriushchenko, Francesco Croce, Nicolas Flammarion, Matthias Hein


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An Efficient Sampling Algorithm for Non-smooth Composite Potentials

Oct 01, 2019
Wenlong Mou, Nicolas Flammarion, Martin J. Wainwright, Peter L. Bartlett


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Improved Bounds for Discretization of Langevin Diffusions: Near-Optimal Rates without Convexity

Jul 25, 2019
Wenlong Mou, Nicolas Flammarion, Martin J. Wainwright, Peter L. Bartlett


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Escaping from saddle points on Riemannian manifolds

Jun 18, 2019
Yue Sun, Nicolas Flammarion, Maryam Fazel

* submitted to NeurIPS 2019 

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Fast Mean Estimation with Sub-Gaussian Rates

Feb 06, 2019
Yeshwanth Cherapanamjeri, Nicolas Flammarion, Peter L. Bartlett


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Is There an Analog of Nesterov Acceleration for MCMC?

Feb 04, 2019
Yi-An Ma, Niladri Chatterji, Xiang Cheng, Nicolas Flammarion, Peter Bartlett, Michael I. Jordan


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Sampling Can Be Faster Than Optimization

Nov 20, 2018
Yi-An Ma, Yuansi Chen, Chi Jin, Nicolas Flammarion, Michael I. Jordan


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Gen-Oja: A Simple and Efficient Algorithm for Streaming Generalized Eigenvector Computation

Nov 20, 2018
Kush Bhatia, Aldo Pacchiano, Nicolas Flammarion, Peter L. Bartlett, Michael I. Jordan

* Accepted at NIPS 2018 

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Averaging Stochastic Gradient Descent on Riemannian Manifolds

Jun 08, 2018
Nilesh Tripuraneni, Nicolas Flammarion, Francis Bach, Michael I. Jordan

* COLT 2018 

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On the Theory of Variance Reduction for Stochastic Gradient Monte Carlo

Feb 15, 2018
Niladri S. Chatterji, Nicolas Flammarion, Yi-An Ma, Peter L. Bartlett, Michael I. Jordan

* 37 pages; 4 figures 

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Stochastic Composite Least-Squares Regression with convergence rate O(1/n)

Feb 21, 2017
Nicolas Flammarion, Francis Bach


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Robust Discriminative Clustering with Sparse Regularizers

Aug 29, 2016
Nicolas Flammarion, Balamurugan Palaniappan, Francis Bach


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Optimal Rates of Statistical Seriation

Aug 01, 2016
Nicolas Flammarion, Cheng Mao, Philippe Rigollet

* V2 corrects an error in Lemma A.1, v3 corrects appendix F on unimodal regression where the bounds now hold with polynomial probability rather than exponential 

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Harder, Better, Faster, Stronger Convergence Rates for Least-Squares Regression

Feb 24, 2016
Aymeric Dieuleveut, Nicolas Flammarion, Francis Bach


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From Averaging to Acceleration, There is Only a Step-size

Apr 07, 2015
Nicolas Flammarion, Francis Bach


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