Edouard Pauwels

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 53

Top Topics

Gradient Method

Convex Optimization

Convergence Analysis

Top Venues

Publications

Franck Iutzeler, Edouard Pauwels, Samuel Vaiter
Derivatives of Stochastic Gradient Descent. CoRR (2024)
Jérôme Bolte, Quoc-Tung Le, Edouard Pauwels, Samuel Vaiter
Geometric and computational hardness of bilevel programming. CoRR (2024)
Jérôme Bolte, Edouard Pauwels, Antonio Silveti-Falls
Differentiating Nonsmooth Solutions to Parametric Monotone Inclusion Problems. SIAM J. Optim. 34 (1) (2024)
Jérôme Bolte, Tam Le, Edouard Pauwels
Subgradient Sampling for Nonsmooth Nonconvex Minimization. SIAM J. Optim. 33 (4) (2023)
Jérôme Bolte, Edouard Pauwels, Samuel Vaiter
One-step differentiation of iterative algorithms. NeurIPS (2023)
Jérôme Bolte, Ryan Boustany, Edouard Pauwels, Béatrice Pesquet-Popescu
On the complexity of nonsmooth automatic differentiation. ICLR (2023)
Edouard Pauwels, Samuel Vaiter
The Derivatives of Sinkhorn-Knopp Converge. SIAM J. Optim. 33 (3) (2023)
Jérôme Bolte, Edouard Pauwels, Samuel Vaiter
One-step differentiation of iterative algorithms. CoRR (2023)
Jérôme Bolte, Edouard Pauwels, Antonio José Silveti-Falls
Differentiating Nonsmooth Solutions to Parametric Monotone Inclusion Problems. CoRR (2022)
Jérôme Bolte, Edouard Pauwels
Curiosities and counterexamples in smooth convex optimization. Math. Program. 195 (1) (2022)
Tong Chen, Jean-Bernard Lasserre, Victor Magron, Edouard Pauwels
A sublevel moment-SOS hierarchy for polynomial optimization. Comput. Optim. Appl. 81 (1) (2022)
Jérôme Bolte, Edouard Pauwels, Samuel Vaiter
Automatic differentiation of nonsmooth iterative algorithms. NeurIPS (2022)
Swann Marx, Edouard Pauwels
Path differentiability of ODE flows. CoRR (2022)
Jérôme Bolte, Edouard Pauwels, Samuel Vaiter
Automatic differentiation of nonsmooth iterative algorithms. CoRR (2022)
Camille Castera, Jérôme Bolte, Cédric Févotte, Edouard Pauwels
Second-Order Step-Size Tuning of SGD for Non-Convex Optimization. Neural Process. Lett. 54 (3) (2022)
Jérôme Bolte, Ryan Boustany, Edouard Pauwels, Béatrice Pesquet-Popescu
Nonsmooth automatic differentiation: a cheap gradient principle and other complexity results. CoRR (2022)
Edouard Pauwels
Incremental Without Replacement Sampling in Nonconvex Optimization. J. Optim. Theory Appl. 190 (1) (2021)
Tong Chen, Jean B. Lasserre, Victor Magron, Edouard Pauwels
Semialgebraic Representation of Monotone Deep Equilibrium Models and Applications to Certification. NeurIPS (2021)
David Bertoin, Jérôme Bolte, Sébastien Gerchinovitz, Edouard Pauwels
Numerical influence of ReLU'(0) on backpropagation. NeurIPS (2021)
Cheik Traoré, Edouard Pauwels
Sequential convergence of AdaGrad algorithm for smooth convex optimization. Oper. Res. Lett. 49 (4) (2021)
Jérôme Bolte, Edouard Pauwels
Conservative set valued fields, automatic differentiation, stochastic gradient methods and deep learning. Math. Program. 188 (1) (2021)
Camille Castera, Jérôme Bolte, Cédric Févotte, Edouard Pauwels
Second-order step-size tuning of SGD for non-convex optimization. CoRR (2021)
Jérôme Bolte, Tam Le, Edouard Pauwels, Antonio Silveti-Falls
Nonsmooth Implicit Differentiation for Machine Learning and Optimization. CoRR (2021)
Edouard Pauwels, Mihai Putinar, Jean-Bernard Lasserre
Data Analysis from Empirical Moments and the Christoffel Function. Found. Comput. Math. 21 (1) (2021)
Jérôme Bolte, Tam Le, Edouard Pauwels, Antonio Silveti-Falls
Nonsmooth Implicit Differentiation for Machine-Learning and Optimization. NeurIPS (2021)
David Bertoin, Jérôme Bolte, Sébastien Gerchinovitz, Edouard Pauwels
Numerical influence of ReLU'(0) on backpropagation. CoRR (2021)
Camille Castera, Jérôme Bolte, Cédric Févotte, Edouard Pauwels
An Inertial Newton Algorithm for Deep Learning. J. Mach. Learn. Res. 22 (2021)
Jérôme Bolte, Edouard Pauwels
A mathematical model for automatic differentiation in machine learning. NeurIPS (2020)
Jérôme Bolte, Edouard Pauwels, Rodolfo Rios-Zertuche
Long term dynamics of the subgradient method for Lipschitz path differentiable functions. CoRR (2020)
Jérôme Bolte, Zheng Chen, Edouard Pauwels
The multiproximal linearization method for convex composite problems. Math. Program. 182 (1) (2020)
Jérôme Bolte, Lilian Glaudin, Edouard Pauwels, Mathieu Serrurier
A Hölderian backtracking method for min-max and min-min problems. CoRR (2020)
Jérôme Bolte, Edouard Pauwels
A mathematical model for automatic differentiation in machine learning. CoRR (2020)
Cheik Traoré, Edouard Pauwels
Sequential convergence of AdaGrad algorithm for smooth convex optimization. CoRR (2020)
Tong Chen, Jean-Bernard Lasserre, Victor Magron, Edouard Pauwels
Polynomial Optimization for Bounding Lipschitz Constants of Deep Networks. CoRR (2020)
Tong Chen, Jean B. Lasserre, Victor Magron, Edouard Pauwels
Semialgebraic Optimization for Lipschitz Constants of ReLU Networks. NeurIPS (2020)
Edouard Pauwels
Incremental Without Replacement Sampling in Nonconvex Optimization. CoRR (2020)
Camille Castera, Jérôme Bolte, Cédric Févotte, Edouard Pauwels
An Inertial Newton Algorithm for Deep Learning. CoRR (2019)
Mai Trang Vu, François Bachoc, Edouard Pauwels
Rate of convergence for geometric inference based on the empirical Christoffel function. CoRR (2019)
Jean B. Lasserre, Edouard Pauwels
The empirical Christoffel function with applications in data analysis. Adv. Comput. Math. 45 (3) (2019)
Jérôme Bolte, Edouard Pauwels
Conservative set valued fields, automatic differentiation, stochastic gradient method and deep learning. CoRR (2019)
Edouard Pauwels, Francis R. Bach, Jean-Philippe Vert
Relating Leverage Scores and Density using Regularized Christoffel Functions. NeurIPS (2018)
Trong Phong Nguyen, Edouard Pauwels, Emile Richard, Bruce W. Suter
Extragradient Method in Optimization: Convergence and Complexity. J. Optim. Theory Appl. 176 (1) (2018)
Jérôme Bolte, Antoine Hochart, Edouard Pauwels
Qualification Conditions in Semialgebraic Programming. SIAM J. Optim. 28 (2) (2018)
Amir Beck, Edouard Pauwels, Shoham Sabach
Primal and dual predicted decrease approximation methods. Math. Program. 167 (1) (2018)
Edouard Pauwels, Francis R. Bach, Jean-Philippe Vert
Relating Leverage Scores and Density using Regularized Christoffel Functions. CoRR (2018)
Edouard Pauwels, Amir Beck, Yonina C. Eldar, Shoham Sabach
On Fienup Methods for Sparse Phase Retrieval. IEEE Trans. Signal Process. 66 (4) (2018)
Jean-Bernard Lasserre, Edouard Pauwels
The empirical Christoffel function in Statistics and Machine Learning. CoRR (2017)
Edouard Pauwels, Amir Beck, Yonina C. Eldar, Shoham Sabach
On Fienup Methods for Regularized Phase Retrieval. CoRR (2017)
Edouard Pauwels
The value function approach to convergence analysis in composite optimization. Oper. Res. Lett. 44 (6) (2016)
Jérôme Bolte, Edouard Pauwels
Majorization-Minimization Procedures and Convergence of SQP Methods for Semi-Algebraic and Tame Programs. Math. Oper. Res. 41 (2) (2016)
Edouard Pauwels, Jean B. Lasserre
Sorting out typicality with the inverse moment matrix SOS polynomial. NIPS (2016)
Edouard Pauwels, Didier Henrion, Jean-Bernard Lasserre
Linear Conic Optimization for Inverse Optimal Control. SIAM J. Control. Optim. 54 (3) (2016)
Jean-Bernard Lasserre, Edouard Pauwels
Sorting out typicality with the inverse moment matrix SOS polynomial. CoRR (2016)
Amir Beck, Edouard Pauwels, Shoham Sabach
The Cyclic Block Conditional Gradient Method for Convex Optimization Problems. SIAM J. Optim. 25 (4) (2015)
Edouard Pauwels, Christian Lajaunie, Jean-Philippe Vert
A Bayesian active learning strategy for sequential experimental design in systems biology. BMC Syst. Biol. 8 (1) (2014)
Edouard Pauwels, Didier Henrion, Jean-Bernard Lasserre
Inverse optimal control with polynomial optimization. CoRR (2014)
Edouard Pauwels, Didier Henrion, Jean-Bernard Lasserre
Inverse optimal control with polynomial optimization. CDC (2014)
Yasuo Tabei, Edouard Pauwels, Véronique Stoven, Kazuhiro Takemoto, Yoshihiro Yamanishi
Identification of chemogenomic features from drug-target interaction networks using interpretable classifiers. Bioinform. 28 (18) (2012)
Sayaka Mizutani, Edouard Pauwels, Véronique Stoven, Susumu Goto, Yoshihiro Yamanishi
Relating drug-protein interaction network with drug side effects. Bioinform. 28 (18) (2012)
Yoshihiro Yamanishi, Edouard Pauwels, Masaaki Kotera
Drug Side-Effect Prediction Based on the Integration of Chemical and Biological Spaces. J. Chem. Inf. Model. 52 (12) (2012)
Yoshihiro Yamanishi, Edouard Pauwels, Hiroto Saigo, Véronique Stoven
Extracting Sets of Chemical Substructures and Protein Domains Governing Drug-Target Interactions. J. Chem. Inf. Model. 51 (5) (2011)
Edouard Pauwels, Véronique Stoven, Yoshihiro Yamanishi
Predicting drug side-effect profiles: a chemical fragment-based approach. BMC Bioinform. 12 (2011)