Edouard Pauwels

75 papers A* 10Journal 62Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	An analytic theory of convolutional neural network inverse problems solvers. CoRR Minh Hai Nguyen, Quoc Bao Do, Edouard Pauwels, Pierre Weiss
2026	J	`jnl`	Geometric and computational hardness of bilevel programming. Math. Program. Jérôme Bolte, Quoc-Tung Le, Edouard Pauwels, Samuel Vaiter
2026	J	`jnl`	The adjoint state method for parametric definable optimization without smoothness or uniqueness. CoRR Jérôme Bolte, Edouard Pauwels, Cheik Traoré
2025	J	`jnl`	A second-order-like optimizer with adaptive gradient scaling for deep learning. Trans. Mach. Learn. Res. Jérôme Bolte, Ryan Boustany, Edouard Pauwels, Andrei I. Purica
2025	J	`jnl`	Convergence of optimizers implies eigenvalues filtering at equilibrium. CoRR Jérôme Bolte, Quoc-Tung Le, Edouard Pauwels
2025	J	`jnl`	How Diffusion Prior Landscapes Shape the Posterior in Blind Deconvolution. CoRR Minh-Hai Nguyen, Edouard Pauwels, Pierre Weiss
2025	J	`jnl`	Learning Theory for Kernel Bilevel Optimization. CoRR Fares El Khoury, Edouard Pauwels, Samuel Vaiter, Michael Arbel
2024	J	`jnl`	A second-order-like optimizer with adaptive gradient scaling for deep learning. CoRR Jérôme Bolte, Ryan Boustany, Edouard Pauwels, Andrei I. Purica
2024	A*	`conf`	Derivatives of Stochastic Gradient Descent in parametric optimization. NeurIPS Franck Iutzeler, Edouard Pauwels, Samuel Vaiter
2024	J	`jnl`	Derivatives of Stochastic Gradient Descent. CoRR Franck Iutzeler, Edouard Pauwels, Samuel Vaiter
2024	J	`jnl`	Differentiating Nonsmooth Solutions to Parametric Monotone Inclusion Problems. SIAM J. Optim. Jérôme Bolte, Edouard Pauwels, Antonio Silveti-Falls
2024	J	`jnl`	Geometric and computational hardness of bilevel programming. CoRR Jérôme Bolte, Quoc-Tung Le, Edouard Pauwels, Samuel Vaiter
2024	J	`jnl`	On the nature of Bregman functions. Oper. Res. Lett. Edouard Pauwels
2024	J	`jnl`	The Iterates of the Frank-Wolfe Algorithm May Not Converge. Math. Oper. Res. Jérôme Bolte, Cyrille W. Combettes, Edouard Pauwels
2023	A*	`conf`	On the complexity of nonsmooth automatic differentiation. ICLR Jérôme Bolte, Ryan Boustany, Edouard Pauwels, Béatrice Pesquet-Popescu
2023	A*	`conf`	One-step differentiation of iterative algorithms. NeurIPS Jérôme Bolte, Edouard Pauwels, Samuel Vaiter
2023	J	`jnl`	One-step differentiation of iterative algorithms. CoRR Jérôme Bolte, Edouard Pauwels, Samuel Vaiter
2023	J	`jnl`	Subgradient Sampling for Nonsmooth Nonconvex Minimization. SIAM J. Optim. Jérôme Bolte, Tam Le, Edouard Pauwels
2023	J	`jnl`	The Derivatives of Sinkhorn-Knopp Converge. SIAM J. Optim. Edouard Pauwels, Samuel Vaiter
2023	J	`jnl`	The backtrack Hölder gradient method with application to min-max and min-min problems. Open J. Math. Optim. Jérôme Bolte, Lilian Glaudin, Edouard Pauwels, Mathieu Serrurier
2022	J	`jnl`	A sublevel moment-SOS hierarchy for polynomial optimization. Comput. Optim. Appl. Tong Chen, Jean-Bernard Lasserre, Victor Magron, Edouard Pauwels
2022	A*	`conf`	Automatic differentiation of nonsmooth iterative algorithms. NeurIPS Jérôme Bolte, Edouard Pauwels, Samuel Vaiter
2022	J	`jnl`	Automatic differentiation of nonsmooth iterative algorithms. CoRR Jérôme Bolte, Edouard Pauwels, Samuel Vaiter
2022	J	`jnl`	Curiosities and counterexamples in smooth convex optimization. Math. Program. Jérôme Bolte, Edouard Pauwels
2022	J	`jnl`	Differentiating Nonsmooth Solutions to Parametric Monotone Inclusion Problems. CoRR Jérôme Bolte, Edouard Pauwels, Antonio José Silveti-Falls
2022	J	`jnl`	Nonsmooth automatic differentiation: a cheap gradient principle and other complexity results. CoRR Jérôme Bolte, Ryan Boustany, Edouard Pauwels, Béatrice Pesquet-Popescu
2022	J	`jnl`	Path differentiability of ODE flows. CoRR Swann Marx, Edouard Pauwels
2022	J	`jnl`	Second-Order Step-Size Tuning of SGD for Non-Convex Optimization. Neural Process. Lett. Camille Castera, Jérôme Bolte, Cédric Févotte, Edouard Pauwels
2021	J	`jnl`	An Inertial Newton Algorithm for Deep Learning. J. Mach. Learn. Res. Camille Castera, Jérôme Bolte, Cédric Févotte, Edouard Pauwels
2021	J	`jnl`	Conservative set valued fields, automatic differentiation, stochastic gradient methods and deep learning. Math. Program. Jérôme Bolte, Edouard Pauwels
2021	J	`jnl`	Data Analysis from Empirical Moments and the Christoffel Function. Found. Comput. Math. Edouard Pauwels, Mihai Putinar, Jean-Bernard Lasserre
2021	J	`jnl`	Incremental Without Replacement Sampling in Nonconvex Optimization. J. Optim. Theory Appl. Edouard Pauwels
2021	J	`jnl`	Nonsmooth Implicit Differentiation for Machine Learning and Optimization. CoRR Jérôme Bolte, Tam Le, Edouard Pauwels, Antonio Silveti-Falls
2021	A*	`conf`	Nonsmooth Implicit Differentiation for Machine-Learning and Optimization. NeurIPS Jérôme Bolte, Tam Le, Edouard Pauwels, Antonio Silveti-Falls
2021	A*	`conf`	Numerical influence of ReLU'(0) on backpropagation. NeurIPS David Bertoin, Jérôme Bolte, Sébastien Gerchinovitz, Edouard Pauwels
2021	J	`jnl`	Numerical influence of ReLU'(0) on backpropagation. CoRR David Bertoin, Jérôme Bolte, Sébastien Gerchinovitz, Edouard Pauwels
2021	J	`jnl`	Second-order step-size tuning of SGD for non-convex optimization. CoRR Camille Castera, Jérôme Bolte, Cédric Févotte, Edouard Pauwels
2021	A*	`conf`	Semialgebraic Representation of Monotone Deep Equilibrium Models and Applications to Certification. NeurIPS Tong Chen, Jean B. Lasserre, Victor Magron, Edouard Pauwels
2021	J	`jnl`	Sequential convergence of AdaGrad algorithm for smooth convex optimization. Oper. Res. Lett. Cheik Traoré, Edouard Pauwels
2020	J	`jnl`	A Hölderian backtracking method for min-max and min-min problems. CoRR Jérôme Bolte, Lilian Glaudin, Edouard Pauwels, Mathieu Serrurier
2020	A*	`conf`	A mathematical model for automatic differentiation in machine learning. NeurIPS Jérôme Bolte, Edouard Pauwels
2020	J	`jnl`	A mathematical model for automatic differentiation in machine learning. CoRR Jérôme Bolte, Edouard Pauwels
2020	J	`jnl`	Incremental Without Replacement Sampling in Nonconvex Optimization. CoRR Edouard Pauwels
2020	J	`jnl`	Long term dynamics of the subgradient method for Lipschitz path differentiable functions. CoRR Jérôme Bolte, Edouard Pauwels, Rodolfo Rios-Zertuche
2020	J	`jnl`	Polynomial Optimization for Bounding Lipschitz Constants of Deep Networks. CoRR Tong Chen, Jean-Bernard Lasserre, Victor Magron, Edouard Pauwels
2020	A*	`conf`	Semialgebraic Optimization for Lipschitz Constants of ReLU Networks. NeurIPS Tong Chen, Jean B. Lasserre, Victor Magron, Edouard Pauwels
2020	J	`jnl`	Sequential convergence of AdaGrad algorithm for smooth convex optimization. CoRR Cheik Traoré, Edouard Pauwels
2020	J	`jnl`	The multiproximal linearization method for convex composite problems. Math. Program. Jérôme Bolte, Zheng Chen, Edouard Pauwels
2019	J	`jnl`	An Inertial Newton Algorithm for Deep Learning. CoRR Camille Castera, Jérôme Bolte, Cédric Févotte, Edouard Pauwels
2019	J	`jnl`	Conservative set valued fields, automatic differentiation, stochastic gradient method and deep learning. CoRR Jérôme Bolte, Edouard Pauwels
2019	J	`jnl`	Rate of convergence for geometric inference based on the empirical Christoffel function. CoRR Mai Trang Vu, François Bachoc, Edouard Pauwels
2019	J	`jnl`	The empirical Christoffel function with applications in data analysis. Adv. Comput. Math. Jean B. Lasserre, Edouard Pauwels
2018	J	`jnl`	Extragradient Method in Optimization: Convergence and Complexity. J. Optim. Theory Appl. Trong Phong Nguyen, Edouard Pauwels, Emile Richard, Bruce W. Suter
2018	J	`jnl`	On Fienup Methods for Sparse Phase Retrieval. IEEE Trans. Signal Process. Edouard Pauwels, Amir Beck, Yonina C. Eldar, Shoham Sabach
2018	J	`jnl`	Primal and dual predicted decrease approximation methods. Math. Program. Amir Beck, Edouard Pauwels, Shoham Sabach
2018	J	`jnl`	Qualification Conditions in Semialgebraic Programming. SIAM J. Optim. Jérôme Bolte, Antoine Hochart, Edouard Pauwels
2018	A*	`conf`	Relating Leverage Scores and Density using Regularized Christoffel Functions. NeurIPS Edouard Pauwels, Francis R. Bach, Jean-Philippe Vert
2018	J	`jnl`	Relating Leverage Scores and Density using Regularized Christoffel Functions. CoRR Edouard Pauwels, Francis R. Bach, Jean-Philippe Vert
2017	J	`jnl`	On Fienup Methods for Regularized Phase Retrieval. CoRR Edouard Pauwels, Amir Beck, Yonina C. Eldar, Shoham Sabach
2017	—	`ch.`	Positivity Certificates in Optimal Control. Geometric and Numerical Foundations of Movements Edouard Pauwels, Didier Henrion, Jean-Bernard Lasserre
2017	J	`jnl`	The empirical Christoffel function in Statistics and Machine Learning. CoRR Jean-Bernard Lasserre, Edouard Pauwels
2016	J	`jnl`	Linear Conic Optimization for Inverse Optimal Control. SIAM J. Control. Optim. Edouard Pauwels, Didier Henrion, Jean-Bernard Lasserre
2016	J	`jnl`	Majorization-Minimization Procedures and Convergence of SQP Methods for Semi-Algebraic and Tame Programs. Math. Oper. Res. Jérôme Bolte, Edouard Pauwels
2016	—	`conf`	Sorting out typicality with the inverse moment matrix SOS polynomial. NIPS Edouard Pauwels, Jean B. Lasserre
2016	J	`jnl`	Sorting out typicality with the inverse moment matrix SOS polynomial. CoRR Jean-Bernard Lasserre, Edouard Pauwels
2016	J	`jnl`	The value function approach to convergence analysis in composite optimization. Oper. Res. Lett. Edouard Pauwels
2015	J	`jnl`	The Cyclic Block Conditional Gradient Method for Convex Optimization Problems. SIAM J. Optim. Amir Beck, Edouard Pauwels, Shoham Sabach
2014	J	`jnl`	A Bayesian active learning strategy for sequential experimental design in systems biology. BMC Syst. Biol. Edouard Pauwels, Christian Lajaunie, Jean-Philippe Vert
2014	—	`conf`	Inverse optimal control with polynomial optimization. CDC Edouard Pauwels, Didier Henrion, Jean-Bernard Lasserre
2014	J	`jnl`	Inverse optimal control with polynomial optimization. CoRR Edouard Pauwels, Didier Henrion, Jean-Bernard Lasserre
2012	J	`jnl`	Drug Side-Effect Prediction Based on the Integration of Chemical and Biological Spaces. J. Chem. Inf. Model. Yoshihiro Yamanishi, Edouard Pauwels, Masaaki Kotera
2012	J	`jnl`	Identification of chemogenomic features from drug-target interaction networks using interpretable classifiers. Bioinform. Yasuo Tabei, Edouard Pauwels, Véronique Stoven, Kazuhiro Takemoto, Yoshihiro Yamanishi
2012	J	`jnl`	Relating drug-protein interaction network with drug side effects. Bioinform. Sayaka Mizutani, Edouard Pauwels, Véronique Stoven, Susumu Goto, Yoshihiro Yamanishi
2011	J	`jnl`	Extracting Sets of Chemical Substructures and Protein Domains Governing Drug-Target Interactions. J. Chem. Inf. Model. Yoshihiro Yamanishi, Edouard Pauwels, Hiroto Saigo, Véronique Stoven
2011	J	`jnl`	Predicting drug side-effect profiles: a chemical fragment-based approach. BMC Bioinform. Edouard Pauwels, Véronique Stoven, Yoshihiro Yamanishi