Jérôme Bolte

Publication Activity (10 Years)

Years Active: 2003-2024
Publications (10 Years): 39

Top Topics

Bilevel Programming

Gradient Method

Convex Optimization

Top Venues

Publications

Jérôme Bolte, Quoc-Tung Le, Edouard Pauwels, Samuel Vaiter
Geometric and computational hardness of bilevel programming. CoRR (2024)
Jérôme Bolte, Laurent Miclo, Stéphane Villeneuve
Swarm gradient dynamics for global optimization: the mean-field limit case. Math. Program. 205 (1) (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)
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)
Jérôme Bolte, Edouard Pauwels, Samuel Vaiter
Automatic differentiation of nonsmooth iterative algorithms. NeurIPS (2022)
Radu-Alexandru Dragomir, Adrien B. Taylor, Alexandre d'Aspremont, Jérôme Bolte
Optimal complexity and certification of Bregman first-order methods. Math. Program. 194 (1) (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)
Radu-Alexandru Dragomir, Alexandre d'Aspremont, Jérôme Bolte
Quartic First-Order Methods for Low-Rank Minimization. J. Optim. Theory Appl. 189 (2) (2021)
David Bertoin, Jérôme Bolte, Sébastien Gerchinovitz, Edouard Pauwels
Numerical influence of ReLU'(0) on backpropagation. NeurIPS (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)
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)
Heinz H. Bauschke, Jérôme Bolte, Jiawei Chen, Marc Teboulle, Xianfu Wang
On Linear Convergence of Non-Euclidean Gradient Methods without Strong Convexity and Lipschitz Gradient Continuity. J. Optim. Theory Appl. 182 (3) (2019)
Camille Castera, Jérôme Bolte, Cédric Févotte, Edouard Pauwels
An Inertial Newton Algorithm for Deep Learning. CoRR (2019)
Radu-Alexandru Dragomir, Adrien Taylor, Alexandre d'Aspremont, Jérôme Bolte
Optimal Complexity and Certification of Bregman First-Order Methods. CoRR (2019)
Jérôme Bolte, Edouard Pauwels
Conservative set valued fields, automatic differentiation, stochastic gradient method and deep learning. CoRR (2019)
Jérôme Bolte, Shoham Sabach, Marc Teboulle, Yakov Vaisbourd
First Order Methods Beyond Convexity and Lipschitz Gradient Continuity with Applications to Quadratic Inverse Problems. SIAM J. Optim. 28 (3) (2018)
Jérôme Bolte, Antoine Hochart, Edouard Pauwels
Qualification Conditions in Semialgebraic Programming. SIAM J. Optim. 28 (2) (2018)
Jérôme Bolte, Shoham Sabach, Marc Teboulle
Nonconvex Lagrangian-Based Optimization: Monitoring Schemes and Global Convergence. Math. Oper. Res. 43 (4) (2018)
Heinz H. Bauschke, Jérôme Bolte, Marc Teboulle
A Descent Lemma Beyond Lipschitz Gradient Continuity: First-Order Methods Revisited and Applications. Math. Oper. Res. 42 (2) (2017)
Jérôme Bolte, Shoham Sabach, Marc Teboulle, Yakov Vaisbourd
First Order Methods beyond Convexity and Lipschitz Gradient Continuity with Applications to Quadratic Inverse Problems. CoRR (2017)
Jérôme Bolte, Trong Phong Nguyen, Juan Peypouquet, Bruce W. Suter
From error bounds to the complexity of first-order descent methods for convex functions. Math. Program. 165 (2) (2017)
Jérôme Bolte, Edouard Pauwels
Majorization-Minimization Procedures and Convergence of SQP Methods for Semi-Algebraic and Tame Programs. Math. Oper. Res. 41 (2) (2016)
Jérôme Bolte, Stéphane Gaubert, Guillaume Vigeral
Definable Zero-Sum Stochastic Games. Math. Oper. Res. 40 (1) (2015)
Jérôme Bolte, Shoham Sabach, Marc Teboulle
Proximal alternating linearized minimization for nonconvex and nonsmooth problems. Math. Program. 146 (1-2) (2014)
Hédy Attouch, Jérôme Bolte, Benar Fux Svaiter
Convergence of descent methods for semi-algebraic and tame problems: proximal algorithms, forward-backward splitting, and regularized Gauss-Seidel methods. Math. Program. 137 (1-2) (2013)
Felipe Alvarez, Jérôme Bolte, J. Frédéric Bonnans, Francisco J. Silva
Asymptotic expansions for interior penalty solutions of control constrained linear-quadratic problems. Math. Program. 135 (1-2) (2012)
Jérôme Bolte, Aris Daniilidis, Adrian S. Lewis
Generic Optimality Conditions for Semialgebraic Convex Programs. Math. Oper. Res. 36 (1) (2011)
Jérôme Bolte, Patrick L. Combettes, Jean-Christophe Pesquet
Alternating proximal algorithm for blind image recovery. ICIP (2010)
Hédy Attouch, Jérôme Bolte, Patrick Redont, Antoine Soubeyran
Proximal Alternating Minimization and Projection Methods for Nonconvex Problems: An Approach Based on the Kurdyka-Lojasiewicz Inequality. Math. Oper. Res. 35 (2) (2010)
Jérôme Bolte, Aris Daniilidis, Adrian S. Lewis
Tame functions are semismooth. Math. Program. 117 (1-2) (2009)
Hédy Attouch, Jérôme Bolte
On the convergence of the proximal algorithm for nonsmooth functions involving analytic features. Math. Program. 116 (1-2) (2009)
Felipe Alvarez, Jérôme Bolte, Julien Munier
A Unifying Local Convergence Result for Newton's Method in Riemannian Manifolds. Found. Comput. Math. 8 (2) (2008)
Jérôme Bolte, Aris Daniilidis, Adrian S. Lewis
The [barred L]ojasiewicz Inequality for Nonsmooth Subanalytic Functions with Applications to Subgradient Dynamical Systems. SIAM J. Optim. 17 (4) (2007)
Jérôme Bolte, Aris Daniilidis, Adrian S. Lewis, Masahiro Shiota
Clarke Subgradients of Stratifiable Functions. SIAM J. Optim. 18 (2) (2007)
Felipe Alvarez, Jérôme Bolte, Olivier Brahic
Hessian Riemannian Gradient Flows in Convex Programming. SIAM J. Control. Optim. 43 (2) (2004)
Jérôme Bolte, Marc Teboulle
Barrier Operators and Associated Gradient-Like Dynamical Systems for Constrained Minimization Problems. SIAM J. Control. Optim. 42 (4) (2003)