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Jérôme Bolte
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- affiliation: University Toulouse Capitole, Toulouse, France
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2020 – today
- 2024
- [j30]Jérôme Bolte, Laurent Miclo, Stéphane Villeneuve
:
Swarm gradient dynamics for global optimization: the mean-field limit case. Math. Program. 205(1): 661-701 (2024) - [j29]Jérôme Bolte, Edouard Pauwels
Differentiating Nonsmooth Solutions to Parametric Monotone Inclusion Problems. SIAM J. Optim. 34(1): 71-97 (2024) - [i16]Jérôme Bolte, Quoc-Tung Le, Edouard Pauwels, Samuel Vaiter:
Geometric and computational hardness of bilevel programming. CoRR abs/2407.12372 (2024) - [i15]Jérôme Bolte, Ryan Boustany, Edouard Pauwels, Andrei I. Purica:
A second-order-like optimizer with adaptive gradient scaling for deep learning. CoRR abs/2410.05871 (2024) - 2023
- [j28]Jérôme Bolte, Tam Le, Edouard Pauwels
Subgradient Sampling for Nonsmooth Nonconvex Minimization. SIAM J. Optim. 33(4): 2542-2569 (2023) - [c7]Jérôme Bolte, Ryan Boustany, Edouard Pauwels, Béatrice Pesquet-Popescu:
On the complexity of nonsmooth automatic differentiation. ICLR 2023 - [c6]Jérôme Bolte, Edouard Pauwels, Samuel Vaiter:
One-step differentiation of iterative algorithms. NeurIPS 2023 - [i14]Jérôme Bolte, Edouard Pauwels, Samuel Vaiter:
One-step differentiation of iterative algorithms. CoRR abs/2305.13768 (2023) - 2022
- [j27]Radu-Alexandru Dragomir
Optimal complexity and certification of Bregman first-order methods. Math. Program. 194(1): 41-83 (2022) - [j26]Jérôme Bolte
Curiosities and counterexamples in smooth convex optimization. Math. Program. 195(1): 553-603 (2022) - [j25]Camille Castera
Second-Order Step-Size Tuning of SGD for Non-Convex Optimization. Neural Process. Lett. 54(3): 1727-1752 (2022) - [c5]Jérôme Bolte, Edouard Pauwels, Samuel Vaiter:
Automatic differentiation of nonsmooth iterative algorithms. NeurIPS 2022 - [i13]Jérôme Bolte, Edouard Pauwels, Samuel Vaiter:
Automatic differentiation of nonsmooth iterative algorithms. CoRR abs/2206.00457 (2022) - [i12]Jérôme Bolte, Ryan Boustany, Edouard Pauwels, Béatrice Pesquet-Popescu:
Nonsmooth automatic differentiation: a cheap gradient principle and other complexity results. CoRR abs/2206.01730 (2022) - [i11]Jérôme Bolte, Edouard Pauwels, Antonio José Silveti-Falls:
Differentiating Nonsmooth Solutions to Parametric Monotone Inclusion Problems. CoRR abs/2212.07844 (2022) - 2021
- [j24]Camille Castera, Jérôme Bolte, Cédric Févotte, Edouard Pauwels:
An Inertial Newton Algorithm for Deep Learning. J. Mach. Learn. Res. 22: 134:1-134:31 (2021) - [j23]Radu-Alexandru Dragomir
Quartic First-Order Methods for Low-Rank Minimization. J. Optim. Theory Appl. 189(2): 341-363 (2021) - [j22]Jérôme Bolte, Edouard Pauwels:
Conservative set valued fields, automatic differentiation, stochastic gradient methods and deep learning. Math. Program. 188(1): 19-51 (2021) - [c4]David Bertoin, Jérôme Bolte, Sébastien Gerchinovitz, Edouard Pauwels:
Numerical influence of ReLU'(0) on backpropagation. NeurIPS 2021: 468-479 - [c3]Jérôme Bolte, Tam Le, Edouard Pauwels, Antonio Silveti-Falls:
Nonsmooth Implicit Differentiation for Machine-Learning and Optimization. NeurIPS 2021: 13537-13549 - [i10]Camille Castera, Jérôme Bolte, Cédric Févotte, Edouard Pauwels:
Second-order step-size tuning of SGD for non-convex optimization. CoRR abs/2103.03570 (2021) - [i9]Jérôme Bolte, Tam Le, Edouard Pauwels, Antonio Silveti-Falls
Nonsmooth Implicit Differentiation for Machine Learning and Optimization. CoRR abs/2106.04350 (2021) - [i8]David Bertoin, Jérôme Bolte, Sébastien Gerchinovitz, Edouard Pauwels:
Numerical influence of ReLU'(0) on backpropagation. CoRR abs/2106.12915 (2021) - 2020
- [j21]Jérôme Bolte, Zheng Chen
The multiproximal linearization method for convex composite problems. Math. Program. 182(1): 1-36 (2020) - [c2]Jérôme Bolte, Edouard Pauwels:
A mathematical model for automatic differentiation in machine learning. NeurIPS 2020 - [i7]Jérôme Bolte, Edouard Pauwels, Rodolfo Rios-Zertuche:
Long term dynamics of the subgradient method for Lipschitz path differentiable functions. CoRR abs/2006.00098 (2020) - [i6]Jérôme Bolte, Edouard Pauwels:
A mathematical model for automatic differentiation in machine learning. CoRR abs/2006.02080 (2020) - [i5]Jérôme Bolte, Lilian Glaudin, Edouard Pauwels, Mathieu Serrurier:
A Hölderian backtracking method for min-max and min-min problems. CoRR abs/2007.08810 (2020)
2010 – 2019
- 2019
- [j20]Heinz H. Bauschke
On Linear Convergence of Non-Euclidean Gradient Methods without Strong Convexity and Lipschitz Gradient Continuity. J. Optim. Theory Appl. 182(3): 1068-1087 (2019) - [i4]Camille Castera, Jérôme Bolte, Cédric Févotte, Edouard Pauwels:
An Inertial Newton Algorithm for Deep Learning. CoRR abs/1905.12278 (2019) - [i3]Jérôme Bolte, Edouard Pauwels:
Conservative set valued fields, automatic differentiation, stochastic gradient method and deep learning. CoRR abs/1909.10300 (2019) - [i2]Radu-Alexandru Dragomir, Adrien B. Taylor, Alexandre d'Aspremont, Jérôme Bolte:
Optimal Complexity and Certification of Bregman First-Order Methods. CoRR abs/1911.08510 (2019) - 2018
- [j19]Jérôme Bolte, Shoham Sabach, Marc Teboulle
Nonconvex Lagrangian-Based Optimization: Monitoring Schemes and Global Convergence. Math. Oper. Res. 43(4): 1210-1232 (2018) - [j18]Jérôme Bolte, Antoine Hochart, Edouard Pauwels:
Qualification Conditions in Semialgebraic Programming. SIAM J. Optim. 28(2): 1867-1891 (2018) - [j17]Jérôme Bolte, Shoham Sabach, Marc Teboulle
First Order Methods Beyond Convexity and Lipschitz Gradient Continuity with Applications to Quadratic Inverse Problems. SIAM J. Optim. 28(3): 2131-2151 (2018) - 2017
- [j16]Heinz H. Bauschke
A Descent Lemma Beyond Lipschitz Gradient Continuity: First-Order Methods Revisited and Applications. Math. Oper. Res. 42(2): 330-348 (2017) - [j15]Jérôme Bolte, Trong Phong Nguyen, Juan Peypouquet
From error bounds to the complexity of first-order descent methods for convex functions. Math. Program. 165(2): 471-507 (2017) - [i1]Jérôme Bolte, Shoham Sabach, Marc Teboulle, Yakov Vaisbourd:
First Order Methods beyond Convexity and Lipschitz Gradient Continuity with Applications to Quadratic Inverse Problems. CoRR abs/1706.06461 (2017) - 2016
- [j14]Jérôme Bolte, Edouard Pauwels:
Majorization-Minimization Procedures and Convergence of SQP Methods for Semi-Algebraic and Tame Programs. Math. Oper. Res. 41(2): 442-465 (2016) - 2015
- [j13]Jérôme Bolte, Stéphane Gaubert, Guillaume Vigeral:
Definable Zero-Sum Stochastic Games. Math. Oper. Res. 40(1): 171-191 (2015) - 2014
- [j12]Jérôme Bolte, Shoham Sabach, Marc Teboulle:
Proximal alternating linearized minimization for nonconvex and nonsmooth problems. Math. Program. 146(1-2): 459-494 (2014) - 2013
- [j11]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): 91-129 (2013) - 2012
- [j10]Felipe Alvarez
Asymptotic expansions for interior penalty solutions of control constrained linear-quadratic problems. Math. Program. 135(1-2): 473-507 (2012) - 2011
- [j9]Jérôme Bolte, Aris Daniilidis
Generic Optimality Conditions for Semialgebraic Convex Programs. Math. Oper. Res. 36(1): 55-70 (2011) - 2010
- [j8]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): 438-457 (2010) - [c1]Jérôme Bolte, Patrick L. Combettes
Alternating proximal algorithm for blind image recovery. ICIP 2010: 1673-1676
2000 – 2009
- 2009
- [j7]Hédy Attouch, Jérôme Bolte:
On the convergence of the proximal algorithm for nonsmooth functions involving analytic features. Math. Program. 116(1-2): 5-16 (2009) - [j6]Jérôme Bolte, Aris Daniilidis
Tame functions are semismooth. Math. Program. 117(1-2): 5-19 (2009) - 2008
- [j5]Felipe Alvarez
A Unifying Local Convergence Result for Newton's Method in Riemannian Manifolds. Found. Comput. Math. 8(2): 197-226 (2008) - 2007
- [j4]Jérôme Bolte, Aris Daniilidis
The [barred L]ojasiewicz Inequality for Nonsmooth Subanalytic Functions with Applications to Subgradient Dynamical Systems. SIAM J. Optim. 17(4): 1205-1223 (2007) - [j3]Jérôme Bolte, Aris Daniilidis
Clarke Subgradients of Stratifiable Functions. SIAM J. Optim. 18(2): 556-572 (2007) - 2004
- [j2]Felipe Alvarez, Jérôme Bolte, Olivier Brahic
Hessian Riemannian Gradient Flows in Convex Programming. SIAM J. Control. Optim. 43(2): 477-501 (2004) - 2003
- [j1]Jérôme Bolte, Marc Teboulle:
Barrier Operators and Associated Gradient-Like Dynamical Systems for Constrained Minimization Problems. SIAM J. Control. Optim. 42(4): 1266-1292 (2003)
Coauthor Index
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