Jérôme Malick

According to our database, Jérôme Malick authored at least 60 papers between 2004 and 2024.

Collaborative distances:

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

2024

Chance-constrained programs with convex underlying functions: a bilevel convex optimization perspective.

Yassine Laguel, Jérôme Malick, Wim van Ackooij

Comput. Optim. Appl., July, 2024

Federated learning with superquantile aggregation for heterogeneous data.

Krishna Pillutla, Yassine Laguel, Jérôme Malick, Zaïd Harchaoui

Mach. Learn., May, 2024

The Rate of Convergence of Bregman Proximal Methods: Local Geometry Versus Regularity Versus Sharpness.

Waïss Azizian, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos

SIAM J. Optim., 2024

What is the Long-Run Distribution of Stochastic Gradient Descent? A Large Deviations Analysis.

Waïss Azizian, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Push-Pull With Device Sampling.

Yu-Guan Hsieh, Yassine Laguel, Franck Iutzeler, Jérôme Malick

IEEE Trans. Autom. Control., December, 2023

Harnessing Structure in Composite Nonsmooth Minimization.

Gilles Bareilles, Franck Iutzeler, Jérôme Malick

SIAM J. Optim., September, 2023

Newton acceleration on manifolds identified by proximal gradient methods.

Gilles Bareilles, Franck Iutzeler, Jérôme Malick

Math. Program., 2023

Exact Generalization Guarantees for (Regularized) Wasserstein Distributionally Robust Models.

Waïss Azizian, Franck Iutzeler, Jérôme Malick

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

2022

Superquantile-Based Learning: A Direct Approach Using Gradient-Based Optimization.

Yassine Laguel, Jérôme Malick, Zaïd Harchaoui

J. Signal Process. Syst., 2022

Multi-Agent Online Optimization with Delays: Asynchronicity, Adaptivity, and Optimism.

Yu-Guan Hsieh, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos

J. Mach. Learn. Res., 2022

On the rate of convergence of Bregman proximal methods in constrained variational inequalities.

Waïss Azizian, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos

CoRR, 2022

2021

Distributed Learning with Sparse Communications by Identification.

Dmitry Grishchenko, Franck Iutzeler, Jérôme Malick, Massih-Reza Amini

SIAM J. Math. Data Sci., 2021

Proximal Gradient Methods with Adaptive Subspace Sampling.

Dmitry Grishchenko, Franck Iutzeler, Jérôme Malick

Math. Oper. Res., 2021

Federated Learning with Heterogeneous Data: A Superquantile Optimization Approach.

Krishna Pillutla, Yassine Laguel, Jérôme Malick, Zaïd Harchaoui

CoRR, 2021

The Last-Iterate Convergence Rate of Optimistic Mirror Descent in Stochastic Variational Inequalities.

Waïss Azizian, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos

Proceedings of the Conference on Learning Theory, 2021

A Superquantile Approach to Federated Learning with Heterogeneous Devices.

Yassine Laguel, Krishna Pillutla, Jérôme Malick, Zaïd Harchaoui

Proceedings of the 55th Annual Conference on Information Sciences and Systems, 2021

Optimization in Open Networks via Dual Averaging.

Yu-Guan Hsieh, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos

Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021

2020

Approximate Joint Diagonalization with Riemannian Optimization on the General Linear Group.

Florent Bouchard, Bijan Afsari, Jérôme Malick, Marco Congedo

SIAM J. Matrix Anal. Appl., 2020

A Distributed Flexible Delay-Tolerant Proximal Gradient Algorithm.

Konstantin Mishchenko, Franck Iutzeler, Jérôme Malick

SIAM J. Optim., 2020

Asynchronous level bundle methods.

Franck Iutzeler, Jérôme Malick, Welington de Oliveira

Math. Program., 2020

Device Heterogeneity in Federated Learning: A Superquantile Approach.

Yassine Laguel, Krishna Pillutla, Jérôme Malick, Zaïd Harchaoui

CoRR, 2020

Randomized Progressive Hedging methods for multi-stage stochastic programming.

Gilles Bareilles, Yassine Laguel, Dmitry Grishchenko, Franck Iutzeler, Jérôme Malick

Ann. Oper. Res., 2020

Explore Aggressively, Update Conservatively: Stochastic Extragradient Methods with Variable Stepsize Scaling.

Yu-Guan Hsieh, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos

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

First-Order Optimization for Superquantile-Based Supervised Learning.

Yassine Laguel, Jérôme Malick, Zaïd Harchaoui

Proceedings of the 30th IEEE International Workshop on Machine Learning for Signal Processing, 2020

2019

Eventual convexity of probability constraints with elliptical distributions.

Wim van Ackooij, Jérôme Malick

Math. Program., 2019

On the convergence of single-call stochastic extra-gradient methods.

Yu-Guan Hsieh, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Model Consistency for Learning with Mirror-Stratifiable Regularizers.

Jalal Fadili, Guillaume Garrigos, Jérôme Malick, Gabriel Peyré

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Riemannian Optimization and Approximate Joint Diagonalization for Blind Source Separation.

Florent Bouchard, Jérôme Malick, Marco Congedo

IEEE Trans. Signal Process., 2018

Sensitivity Analysis for Mirror-Stratifiable Convex Functions.

Jalal Fadili, Jérôme Malick, Gabriel Peyré

SIAM J. Optim., 2018

On the Proximal Gradient Algorithm with Alternated Inertia.

Franck Iutzeler, Jérôme Malick

J. Optim. Theory Appl., 2018

Asynchronous Distributed Learning with Sparse Communications and Identification.

Dmitry Grishchenko, Franck Iutzeler, Jérôme Malick, Massih-Reza Amini

CoRR, 2018

A Delay-tolerant Proximal-Gradient Algorithm for Distributed Learning.

Konstantin Mishchenko, Franck Iutzeler, Jérôme Malick, Massih-Reza Amini

Proceedings of the 35th International Conference on Machine Learning, 2018

2017

BiqCrunch: A Semidefinite Branch-and-Bound Method for Solving Binary Quadratic Problems.

Nathan Krislock, Jérôme Malick, Frédéric Roupin

ACM Trans. Math. Softw., 2017

Second-order differentiability of probability functions.

Wim van Ackooij, Jérôme Malick

Optim. Lett., 2017

Uncontrolled inexact information within bundle methods.

Jérôme Malick, Welington de Oliveira, Sofia Zaourar

EURO J. Comput. Optim., 2017

Regularized decomposition of large scale block-structured robust optimization problems.

Wim van Ackooij, Nicolas Lebbe, Jérôme Malick

Comput. Manag. Sci., 2017

Approximate Joint Diagonalization According to the Natural Riemannian Distance.

Florent Bouchard, Jérôme Malick, Marco Congedo

Proceedings of the Latent Variable Analysis and Signal Separation, 2017

Variational-analysis look at combinatorial optimization, and other selected topics in optimization.

Jérôme Malick

, 2017

2016

Computational results of a semidefinite branch-and-bound algorithm for k-cluster.

Nathan Krislock, Jérôme Malick, Frédéric Roupin

Comput. Oper. Res., 2016

Decomposition algorithm for large-scale two-stage unit-commitment.

Wim van Ackooij, Jérôme Malick

Ann. Oper. Res., 2016

Approximate joint diagonalization within the Riemannian geometry framework.

Florent Bouchard, Louis Korczowski, Jérôme Malick, Marco Congedo

Proceedings of the 24th European Signal Processing Conference, 2016

2015

Cut-Generating Functions and <i>S</i>-Free Sets.

Michele Conforti, Gérard Cornuéjols, Aris Daniilidis, Claude Lemaréchal, Jérôme Malick

Math. Oper. Res., 2015

2014

Improved semidefinite bounding procedure for solving Max-Cut problems to optimality.

Nathan Krislock, Jérôme Malick, Frédéric Roupin

Math. Program., 2014

2013

On the bridge between combinatorial optimization and nonlinear optimization: a family of semidefinite bounds for 0-1 quadratic problems leading to quasi-Newton methods.

Jérôme Malick, Frédéric Roupin

Math. Program., 2013

Prices stabilization for inexact unit-commitment problems.

Sofia Zaourar, Jérôme Malick

Math. Methods Oper. Res., 2013

Cut-Generating Functions.

Michele Conforti, Gérard Cornuéjols, Aris Daniilidis, Claude Lemaréchal, Jérôme Malick

Proceedings of the Integer Programming and Combinatorial Optimization, 2013

2012

Projection-like Retractions on Matrix Manifolds.

Pierre-Antoine Absil, Jérôme Malick

SIAM J. Optim., 2012

Solving k-cluster problems to optimality with semidefinite programming.

Jérôme Malick, Frédéric Roupin

Math. Program., 2012

A Fresh Variational-Analysis Look at the Positive Semidefinite Matrices World.

Jean-Baptiste Hiriart-Urruty, Jérôme Malick

J. Optim. Theory Appl., 2012

Lifted coordinate descent for learning with trace-norm regularization.

Miroslav Dudík, Zaïd Harchaoui, Jérôme Malick

Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Descentwise inexact proximal algorithms for smooth optimization.

Marc Fuentes, Jérôme Malick, Claude Lemaréchal

Comput. Optim. Appl., 2012

Large-scale image classification with trace-norm regularization.

Zaïd Harchaoui, Matthijs Douze, Mattis Paulin, Miroslav Dudík, Jérôme Malick

Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition, 2012

2011

Projection methods for conic feasibility problems: applications to polynomial sum-of-squares decompositions.

Didier Henrion, Jérôme Malick

Optim. Methods Softw., 2011

2010

Numerical Study of Semidefinite Bounds for the k-cluster Problem.

Jérôme Malick, Frédéric Roupin

Electron. Notes Discret. Math., 2010

2009

Regularization Methods for Semidefinite Programming.

Jérôme Malick, Janez Povh, Franz Rendl, Angelika Wiegele

SIAM J. Optim., 2009

Local Linear Convergence for Alternating and Averaged Nonconvex Projections.

Adrian S. Lewis, D. Russell Luke, Jérôme Malick

Found. Comput. Math., 2009

2008

Alternating Projections on Manifolds.

Adrian S. Lewis, Jérôme Malick

Math. Oper. Res., 2008

2007

The spherical constraint in Boolean quadratic programs.

Jérôme Malick

J. Glob. Optim., 2007

2005

Newton methods for nonsmooth convex minimization: connections among U-Lagrangian, Riemannian Newton and SQP methods.

Scott A. Miller, Jérôme Malick

Math. Program., 2005

2004

A Dual Approach to Semidefinite Least-Squares Problems.

Jérôme Malick

SIAM J. Matrix Anal. Appl., 2004