Jérôme Malick

Orcid: 0000-0003-0371-0457

According to our database1, Jérôme Malick authored at least 56 papers between 2004 and 2023.

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Bibliography

2023
Push-Pull With Device Sampling.
IEEE Trans. Autom. Control., December, 2023

Harnessing Structure in Composite Nonsmooth Minimization.
SIAM J. Optim., September, 2023

Newton acceleration on manifolds identified by proximal gradient methods.
Math. Program., 2023

Exact Generalization Guarantees for (Regularized) Wasserstein Distributionally Robust Models.
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.
J. Signal Process. Syst., 2022

Multi-Agent Online Optimization with Delays: Asynchronicity, Adaptivity, and Optimism.
J. Mach. Learn. Res., 2022

On the rate of convergence of Bregman proximal methods in constrained variational inequalities.
CoRR, 2022

2021
Distributed Learning with Sparse Communications by Identification.
SIAM J. Math. Data Sci., 2021

Proximal Gradient Methods with Adaptive Subspace Sampling.
Math. Oper. Res., 2021

Federated Learning with Heterogeneous Data: A Superquantile Optimization Approach.
CoRR, 2021

The Last-Iterate Convergence Rate of Optimistic Mirror Descent in Stochastic Variational Inequalities.
Proceedings of the Conference on Learning Theory, 2021

A Superquantile Approach to Federated Learning with Heterogeneous Devices.
Proceedings of the 55th Annual Conference on Information Sciences and Systems, 2021

Optimization in Open Networks via Dual Averaging.
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.
SIAM J. Matrix Anal. Appl., 2020

A Distributed Flexible Delay-Tolerant Proximal Gradient Algorithm.
SIAM J. Optim., 2020

Asynchronous level bundle methods.
Math. Program., 2020

Device Heterogeneity in Federated Learning: A Superquantile Approach.
CoRR, 2020

Randomized Progressive Hedging methods for multi-stage stochastic programming.
Ann. Oper. Res., 2020

Explore Aggressively, Update Conservatively: Stochastic Extragradient Methods with Variable Stepsize Scaling.
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.
Proceedings of the 30th IEEE International Workshop on Machine Learning for Signal Processing, 2020

2019
Eventual convexity of probability constraints with elliptical distributions.
Math. Program., 2019

On the convergence of single-call stochastic extra-gradient methods.
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.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
Riemannian Optimization and Approximate Joint Diagonalization for Blind Source Separation.
IEEE Trans. Signal Process., 2018

Sensitivity Analysis for Mirror-Stratifiable Convex Functions.
SIAM J. Optim., 2018

On the Proximal Gradient Algorithm with Alternated Inertia.
J. Optim. Theory Appl., 2018

Asynchronous Distributed Learning with Sparse Communications and Identification.
CoRR, 2018

A Delay-tolerant Proximal-Gradient Algorithm for Distributed Learning.
Proceedings of the 35th International Conference on Machine Learning, 2018

2017
BiqCrunch: A Semidefinite Branch-and-Bound Method for Solving Binary Quadratic Problems.
ACM Trans. Math. Softw., 2017

Second-order differentiability of probability functions.
Optim. Lett., 2017

Uncontrolled inexact information within bundle methods.
EURO J. Comput. Optim., 2017

Regularized decomposition of large scale block-structured robust optimization problems.
Comput. Manag. Sci., 2017

Approximate Joint Diagonalization According to the Natural Riemannian Distance.
Proceedings of the Latent Variable Analysis and Signal Separation, 2017

Variational-analysis look at combinatorial optimization, and other selected topics in optimization.
, 2017

2016
Computational results of a semidefinite branch-and-bound algorithm for k-cluster.
Comput. Oper. Res., 2016

Decomposition algorithm for large-scale two-stage unit-commitment.
Ann. Oper. Res., 2016

Approximate joint diagonalization within the Riemannian geometry framework.
Proceedings of the 24th European Signal Processing Conference, 2016

2015
Cut-Generating Functions and <i>S</i>-Free Sets.
Math. Oper. Res., 2015

2014
Improved semidefinite bounding procedure for solving Max-Cut problems to optimality.
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.
Math. Program., 2013

Prices stabilization for inexact unit-commitment problems.
Math. Methods Oper. Res., 2013

Cut-Generating Functions.
Proceedings of the Integer Programming and Combinatorial Optimization, 2013

2012
Projection-like Retractions on Matrix Manifolds.
SIAM J. Optim., 2012

Solving k-cluster problems to optimality with semidefinite programming.
Math. Program., 2012

A Fresh Variational-Analysis Look at the Positive Semidefinite Matrices World.
J. Optim. Theory Appl., 2012

Lifted coordinate descent for learning with trace-norm regularization.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

Descentwise inexact proximal algorithms for smooth optimization.
Comput. Optim. Appl., 2012

Large-scale image classification with trace-norm regularization.
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.
Optim. Methods Softw., 2011

2010
Numerical Study of Semidefinite Bounds for the k-cluster Problem.
Electron. Notes Discret. Math., 2010

2009
Regularization Methods for Semidefinite Programming.
SIAM J. Optim., 2009

Local Linear Convergence for Alternating and Averaged Nonconvex Projections.
Found. Comput. Math., 2009

2008
Alternating Projections on Manifolds.
Math. Oper. Res., 2008

2007
The spherical constraint in Boolean quadratic programs.
J. Glob. Optim., 2007

2005
Newton methods for nonsmooth convex minimization: connections among U-Lagrangian, Riemannian Newton and SQP methods.
Math. Program., 2005

2004
A Dual Approach to Semidefinite Least-Squares Problems.
SIAM J. Matrix Anal. Appl., 2004


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