Jérôme Bolte

According to our database, Jérôme Bolte authored at least 45 papers between 2003 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Swarm gradient dynamics for global optimization: the mean-field limit case.

Jérôme Bolte, Laurent Miclo, Stéphane Villeneuve

Math. Program., May, 2024

Differentiating Nonsmooth Solutions to Parametric Monotone Inclusion Problems.

Jérôme Bolte, Edouard Pauwels, Antonio Silveti-Falls

SIAM J. Optim., March, 2024

The Iterates of the Frank-Wolfe Algorithm May Not Converge.

Jérôme Bolte, Cyrille W. Combettes, Edouard Pauwels

Math. Oper. Res., 2024

A second-order-like optimizer with adaptive gradient scaling for deep learning.

Jérôme Bolte, Ryan Boustany, Edouard Pauwels, Andrei I. Purica

CoRR, 2024

Geometric and computational hardness of bilevel programming.

Jérôme Bolte, Quoc-Tung Le, Edouard Pauwels, Samuel Vaiter

CoRR, 2024

2023

Subgradient Sampling for Nonsmooth Nonconvex Minimization.

Jérôme Bolte, Tam Le, Edouard Pauwels

SIAM J. Optim., December, 2023

The backtrack Hölder gradient method with application to min-max and min-min problems.

Jérôme Bolte, Lilian Glaudin, Edouard Pauwels, Mathieu Serrurier

Open J. Math. Optim., 2023

One-step differentiation of iterative algorithms.

Jérôme Bolte, Edouard Pauwels, Samuel Vaiter

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

On the complexity of nonsmooth automatic differentiation.

Jérôme Bolte, Ryan Boustany, Edouard Pauwels, Béatrice Pesquet-Popescu

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Second-Order Step-Size Tuning of SGD for Non-Convex Optimization.

Camille Castera, Jérôme Bolte, Cédric Févotte, Edouard Pauwels

Neural Process. Lett., 2022

Optimal complexity and certification of Bregman first-order methods.

Radu-Alexandru Dragomir, Adrien B. Taylor, Alexandre d'Aspremont, Jérôme Bolte

Math. Program., 2022

Curiosities and counterexamples in smooth convex optimization.

Jérôme Bolte, Edouard Pauwels

Math. Program., 2022

Nonsmooth automatic differentiation: a cheap gradient principle and other complexity results.

Jérôme Bolte, Ryan Boustany, Edouard Pauwels, Béatrice Pesquet-Popescu

CoRR, 2022

Automatic differentiation of nonsmooth iterative algorithms.

Jérôme Bolte, Edouard Pauwels, Samuel Vaiter

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Conservative set valued fields, automatic differentiation, stochastic gradient methods and deep learning.

Jérôme Bolte, Edouard Pauwels

Math. Program., 2021

Quartic First-Order Methods for Low-Rank Minimization.

Radu-Alexandru Dragomir, Alexandre d'Aspremont, Jérôme Bolte

J. Optim. Theory Appl., 2021

An Inertial Newton Algorithm for Deep Learning.

Camille Castera, Jérôme Bolte, Cédric Févotte, Edouard Pauwels

J. Mach. Learn. Res., 2021

Nonsmooth Implicit Differentiation for Machine-Learning and Optimization.

Jérôme Bolte, Tam Le, Edouard Pauwels, Antonio Silveti-Falls

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Numerical influence of ReLU'(0) on backpropagation.

David Bertoin, Jérôme Bolte, Sébastien Gerchinovitz, Edouard Pauwels

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

The multiproximal linearization method for convex composite problems.

Jérôme Bolte, Zheng Chen, Edouard Pauwels

Math. Program., 2020

A Hölderian backtracking method for min-max and min-min problems.

Jérôme Bolte, Lilian Glaudin, Edouard Pauwels, Mathieu Serrurier

CoRR, 2020

Long term dynamics of the subgradient method for Lipschitz path differentiable functions.

Jérôme Bolte, Edouard Pauwels, Rodolfo Rios-Zertuche

CoRR, 2020

A mathematical model for automatic differentiation in machine learning.

Jérôme Bolte, Edouard Pauwels

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

On Linear Convergence of Non-Euclidean Gradient Methods without Strong Convexity and Lipschitz Gradient Continuity.

Heinz H. Bauschke, Jérôme Bolte, Jiawei Chen, Marc Teboulle, Xianfu Wang

J. Optim. Theory Appl., 2019

Conservative set valued fields, automatic differentiation, stochastic gradient method and deep learning.

Jérôme Bolte, Edouard Pauwels

CoRR, 2019

2018

First Order Methods Beyond Convexity and Lipschitz Gradient Continuity with Applications to Quadratic Inverse Problems.

Jérôme Bolte, Shoham Sabach, Marc Teboulle, Yakov Vaisbourd

SIAM J. Optim., 2018

Qualification Conditions in Semialgebraic Programming.

Jérôme Bolte, Antoine Hochart, Edouard Pauwels

SIAM J. Optim., 2018

Nonconvex Lagrangian-Based Optimization: Monitoring Schemes and Global Convergence.

Jérôme Bolte, Shoham Sabach, Marc Teboulle

Math. Oper. Res., 2018

2017

From error bounds to the complexity of first-order descent methods for convex functions.

Jérôme Bolte, Trong Phong Nguyen, Juan Peypouquet, Bruce W. Suter

Math. Program., 2017

A Descent Lemma Beyond Lipschitz Gradient Continuity: First-Order Methods Revisited and Applications.

Heinz H. Bauschke, Jérôme Bolte, Marc Teboulle

Math. Oper. Res., 2017

2016

Majorization-Minimization Procedures and Convergence of SQP Methods for Semi-Algebraic and Tame Programs.

Jérôme Bolte, Edouard Pauwels

Math. Oper. Res., 2016

2015

Definable Zero-Sum Stochastic Games.

Jérôme Bolte, Stéphane Gaubert, Guillaume Vigeral

Math. Oper. Res., 2015

2014

Proximal alternating linearized minimization for nonconvex and nonsmooth problems.

Jérôme Bolte, Shoham Sabach, Marc Teboulle

Math. Program., 2014

2013

Convergence of descent methods for semi-algebraic and tame problems: proximal algorithms, forward-backward splitting, and regularized Gauss-Seidel methods.

Hédy Attouch, Jérôme Bolte, Benar Fux Svaiter

Math. Program., 2013

2012

Asymptotic expansions for interior penalty solutions of control constrained linear-quadratic problems.

Felipe Alvarez, Jérôme Bolte, J. Frédéric Bonnans, Francisco J. Silva

Math. Program., 2012

2011

Generic Optimality Conditions for Semialgebraic Convex Programs.

Jérôme Bolte, Aris Daniilidis, Adrian S. Lewis

Math. Oper. Res., 2011

2010

Proximal Alternating Minimization and Projection Methods for Nonconvex Problems: An Approach Based on the Kurdyka-Lojasiewicz Inequality.

Hédy Attouch, Jérôme Bolte, Patrick Redont, Antoine Soubeyran

Math. Oper. Res., 2010

Alternating proximal algorithm for blind image recovery.

Jérôme Bolte, Patrick L. Combettes, Jean-Christophe Pesquet

Proceedings of the International Conference on Image Processing, 2010

2009

Tame functions are semismooth.

Jérôme Bolte, Aris Daniilidis, Adrian S. Lewis

Math. Program., 2009

On the convergence of the proximal algorithm for nonsmooth functions involving analytic features.

Hédy Attouch, Jérôme Bolte

Math. Program., 2009

2008

A Unifying Local Convergence Result for Newton's Method in Riemannian Manifolds.

Felipe Alvarez, Jérôme Bolte, Julien Munier

Found. Comput. Math., 2008

2007

Clarke Subgradients of Stratifiable Functions.

Jérôme Bolte, Aris Daniilidis, Adrian S. Lewis, Masahiro Shiota

SIAM J. Optim., 2007

The [barred L]ojasiewicz Inequality for Nonsmooth Subanalytic Functions with Applications to Subgradient Dynamical Systems.

Jérôme Bolte, Aris Daniilidis, Adrian S. Lewis

SIAM J. Optim., 2007

2004

Hessian Riemannian Gradient Flows in Convex Programming.

Felipe Alvarez, Jérôme Bolte, Olivier Brahic

SIAM J. Control. Optim., 2004

2003

Barrier Operators and Associated Gradient-Like Dynamical Systems for Constrained Minimization Problems.

Jérôme Bolte, Marc Teboulle

SIAM J. Control. Optim., 2003