J. Malick

发表

Geometrical interpretation of the predictor-corrector type algorithms in structured optimization problems

A. Daniilidis, W. Hare, J. Malick, 2006 .

Prox-Regularity of Spectral Functions and Spectral Sets

Hristo S. Sendov, A. Lewis, A. Daniilidis, 2008 .

Locally symmetric submanifolds lift to spectral manifolds

Hristo S. Sendov, A. Daniilidis, J. Malick, 2012, 1212.3936.

Local convergence for alternating and averaged nonconvex projections

A. Lewis, J. Malick, R. Luke, 2007, 0709.0109.

Projection-like Retractions on Matrix Manifolds

Jérôme Malick, Pierre-Antoine Absil, P. Absil, 2012, SIAM J. Optim..

Alternating Projections on Manifolds

Adrian S. Lewis, Jérôme Malick, A. Lewis, 2008, Math. Oper. Res..

Filling the Gap Between Lower-C 1 and Lower-C 2 Functions

A. Daniilidis, J. Malick, 2005 .

Lifted coordinate descent for learning with trace-norm regularization

Zaïd Harchaoui, Miroslav Dudík, Jérôme Malick, 2012, AISTATS.

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

Jérôme Malick, Scott A. Miller, J. Malick, 2005, Math. Program..

A smoothing approach for composite conditional gradient with nonsmooth loss

Z. Harchaoui, J. Malick, F. Pierucci, 2014 .

Projection methods in conic optimization

J. Malick, D. Henrion, 2011, 1103.1511.

A formulation of the linear discrete Coulomb friction problem via convex optimization

C. Lemaréchal, V. Acary, J. Malick, 2011 .

functions and spectral sets

Hristo S. Sendov, A. Lewis, A. Daniilidis, 2008 .

Spectral ( Isotropic ) Manifolds and Their Dimension Aris DANIILIDIS ,

Hristo S. Sendov, J. Malick, A. Danilidis, 2017 .

Solving stochastic programming problems with randomized scenario sampling

Dmitry Grishchenko, Yassine Laguel, Franck Iutzeler, 2020 .

Push-Pull with Device Sampling

J. Malick, F. Iutzeler, Yassine Laguel, 2022, ArXiv.

Harnessing structure in composite nonsmooth minimization

J. Malick, F. Iutzeler, Gilles Bareilles, 2022, 2206.15053.

Projection methods for conic feasibility problems; applications to sum-of-squares decompositions

J. Malick, D. Henrion, 2015 .

Newton acceleration on manifolds identified by proximal gradient methods

J. Malick, F. Iutzeler, Gilles Bareilles, 2020, Mathematical Programming.

Regularization for Wasserstein Distributionally Robust Optimization

J. Malick, F. Iutzeler, Waïss Azizian, 2022, 2205.08826.

BiqCrunch

J. Malick, Nathan Krislock, Frédéric Roupin, 2017 .

A Distributed Flexible Delay-Tolerant Proximal Gradient Algorithm

J. Malick, Konstantin Mishchenko, F. Iutzeler, 2018, SIAM J. Optim..

Prices stabilization for inexact unit-commitment problems

J. Malick, Sofia Zaourar, 2013, Mathematical Methods of Operations Research.

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

J. Malick, P. Mertikopoulos, F. Iutzeler, 2022, ArXiv.

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

J. Malick, Nathan Krislock, Frédéric Roupin, 2012, Mathematical Programming.

Eventual convexity of probability constraints with elliptical distributions

J. Malick, W. van Ackooij, 2018, Mathematical Programming.

Descentwise inexact proximal algorithms for smooth optimization

C. Lemaréchal, J. Malick, M. Fuentes, 2012, Computational optimization and applications.

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

J. Malick, W. van Ackooij, 2015, Annals of Operations Research.

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

Z. Harchaoui, J. Malick, Yassine Laguel, 2022, Journal of Signal Processing Systems.

Federated learning with superquantile aggregation for heterogeneous data

Z. Harchaoui, J. Malick, Krishna Pillutla, 2021, Machine Learning.

Differentially Private Federated Quantiles with the Distributed Discrete Gaussian Mechanism

Z. Harchaoui, J. Malick, Krishna Pillutla, 2022 .

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

J. Malick, Frédéric Roupin, 2012, Mathematical programming.

Regularized decomposition of large scale block-structured robust optimization problems

J. Malick, W. van Ackooij, N. Lebbe, 2017, Computational Management Science.

Second-order differentiability of probability functions

J. Malick, W. van Ackooij, 2016, Optimization Letters.

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

J. Malick, P. Mertikopoulos, F. Iutzeler, 2020, NeurIPS.

On the Proximal Gradient Algorithm with Alternated Inertia

J. Malick, F. Iutzeler, 2018, Journal of Optimization Theory and Applications.

Sensitivity Analysis for Mirror-Stratifiable Convex Functions pdf

Mohamed-Jalal Fadili, Jérôme Malick, Gabriel Peyré, 2017, SIAM J. Optim..

Nonsmoothness in Machine Learning: Specific Structure, Proximal Identification, and Applications

J. Malick, F. Iutzeler, 2020, Set-Valued and Variational Analysis.

First-Order Optimization for Superquantile-Based Supervised Learning

Yassine Laguel, J'erome Malick, Zaid Harchaoui, 2020, 2020 IEEE 30th International Workshop on Machine Learning for Signal Processing (MLSP).

On the Proximal Gradient Algorithm with Alternated Inertia

Jérôme Malick, Franck Iutzeler, J. Malick, 2018, Journal of Optimization Theory and Applications.

Clarke Generalized Jacobian of the Projection onto the Cone of Positive Semidefinite Matrices

Jérôme Malick, Hristo S. Sendov, J. Malick, 2006 .

Riemannian Optimization and Approximate Joint Diagonalization for Blind Source Separation

Marco Congedo, Florent Bouchard, Jérôme Malick, 2018, IEEE Transactions on Signal Processing.

A Superquantile Approach to Federated Learning with Heterogeneous Devices

Z. Harchaoui, J. Malick, Krishna Pillutla, 2021, 2021 55th Annual Conference on Information Sciences and Systems (CISS).

Approximate joint diagonalization within the Riemannian geometry framework

Jérôme Malick, Marco Congedo, Louis Korczowski, 2016, 2016 24th European Signal Processing Conference (EUSIPCO).

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

J. Malick, P. Mertikopoulos, F. Iutzeler, 2020, J. Mach. Learn. Res..

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

Jérôme Malick, Wim van Ackooij, J. Malick, 2016, Ann. Oper. Res..

Prices stabilization for inexact unit-commitment problems

Jérôme Malick, Sofia Zaourar, J. Malick, 2013, Math. Methods Oper. Res..

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

Frédéric Roupin, Jérôme Malick, Nathan Krislock, 2014, Math. Program..

Regularization Methods for Semidefinite Programming

Franz Rendl, Jérôme Malick, Janez Povh, 2009, SIAM J. Optim..

BiqCrunch

J. Malick, Nathan Krislock, Frédéric Roupin, 2017, ACM Trans. Math. Softw..

Push-Pull with Device Sampling

J. Malick, F. Iutzeler, Yassine Laguel, 2022, IEEE Transactions on Automatic Control.

Device Heterogeneity in Federated Learning: A Superquantile Approach pdf

Yassine Laguel, J'erome Malick, Zaid Harchaoui, 2020, ArXiv.

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

Yassine Laguel, J'erome Malick, Zaid Harchaoui, 2022, Journal of Signal Processing Systems.

Superquantiles at Work: Machine Learning Applications and Efficient Subgradient Computation

Jérôme Malick, Yassine Laguel, Krishna Pillutla, 2021, Set-Valued and Variational Analysis.

Local Linear Convergence for Alternating and Averaged Nonconvex Projections

Adrian S. Lewis, Jérôme Malick, D. R. Luke, 2009, Found. Comput. Math..

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

Panayotis Mertikopoulos, Franck Iutzeler, J'erome Malick, 2021, COLT.

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

Jérôme Malick, Didier Henrion, J. Malick, 2011, Optim. Methods Softw..

Federated Learning with Heterogeneous Data: A Superquantile Optimization Approach pdf

Yassine Laguel, Krishna Pillutla, J'erome Malick, 2021, ArXiv.

Exact Generalization Guarantees for (Regularized) Wasserstein Distributionally Robust Models

J. Malick, F. Iutzeler, Waïss Azizian, 2023, NeurIPS.

Regularization for Wasserstein distributionally robust optimization

J. Malick, F. Iutzeler, Waïss Azizian, 2022, ESAIM: Control, Optimisation and Calculus of Variations.

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

J. Malick, P. Mertikopoulos, F. Iutzeler, 2019, NeurIPS.

Modeling, Simulating, Controlling Non-Regular Dynamical Systems

Pierre-Brice Wieber, Vincent Acary, Jérôme Malick, 2004 .

Optimization in Open Networks via Dual Averaging pdf

Panayotis Mertikopoulos, Franck Iutzeler, Yu-Guan Hsieh, 2021, 2021 60th IEEE Conference on Decision and Control (CDC).

Spectral (isotropic) manifolds and their dimension

Aris Daniilidis, Hristo S. Sendov, Jerome Malick, 2016 .

Large-scale image classification with trace-norm regularization

Matthijs Douze, Zaïd Harchaoui, Miroslav Dudík, 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

Asynchronous level bundle methods

Franck Iutzeler, Jérôme Malick, Welington de Oliveira, 2019, Mathematical Programming.

A Delay-tolerant Proximal-Gradient Algorithm for Distributed Learning

Jérôme Malick, Massih-Reza Amini, Franck Iutzeler, 2018, ICML.

Approximate Joint Diagonalization According to the Natural Riemannian Distance

Jérôme Malick, Marco Congedo, Florent Bouchard, 2017, LVA/ICA.

Device Heterogeneity in Federated Learning: A Superquantile Approach

Z. Harchaoui, J. Malick, Krishna Pillutla, 2020, Machine Learning.

The rate of convergence of Bregman proximal methods: Local geometry vs. regularity vs. sharpness

J. Malick, P. Mertikopoulos, F. Iutzeler, 2022, 2211.08043.

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

Frédéric Roupin, Jérôme Malick, Nathan Krislock, 2016, Comput. Oper. Res..

The spherical constraint in Boolean quadratic programs

Jérôme Malick, J. Malick, 2007, J. Glob. Optim..

Harnessing Structure in Composite Nonsmooth Minimization

J. Malick, F. Iutzeler, Gilles Bareilles, 2022, SIAM J. Optim..

Asynchronous Distributed Learning with Sparse Communications and Identification pdf

Jérôme Malick, Massih-Reza Amini, Dmitry Grishchenko, 2018, ArXiv.

A Dual Approach to Semidefinite Least-Squares Problems

Jérôme Malick, J. Malick, 2004, SIAM J. Matrix Anal. Appl..

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

Frédéric Roupin, Jérôme Malick, J. Malick, 2013, Math. Program..

Uncontrolled inexact information within bundle methods

Jérôme Malick, Sofia Zaourar, Welington de Oliveira, 2017, EURO J. Comput. Optim..

Quadratic stabilization of Benders decomposition

Jérôme Malick, Sofia Zaourar, J. Malick, 2014 .

On the Convexity of Level-sets of Probability Functions

Yassine Laguel, Wim van Ackooij, Guilherme Ramalho, 2021, 2102.04052.

Eventual convexity of probability constraints with elliptical distributions

Jérôme Malick, Wim van Ackooij, J. Malick, 2019, Math. Program..

Regularized decomposition of large scale block-structured robust optimization problems

Jérôme Malick, Wim van Ackooij, Nicolas Lebbe, 2017, Comput. Manag. Sci..

Descentwise inexact proximal algorithms for smooth optimization

Jérôme Malick, Claude Lemaréchal, Marc Fuentes, 2012, Comput. Optim. Appl..

Randomized Progressive Hedging methods for multi-stage stochastic programming pdf

Dmitry Grishchenko, Yassine Laguel, J'erome Malick, 2020, Annals of Operations Research.

The short-term electricity production management problem at EDF

Jérôme Malick, Claude Lemaréchal, Grace Hechme-Doukopoulos, 2010 .

OPTIMIZATION USING UNCONTROLLED INEXACT INFORMATION

J. Malick, W. Oliveira, JÉRÔME MALICK, 2013 .

Solving \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$k$$\end{document}-cluster problems to optimality with semidefi

Frédéric Roupin, Jérôme Malick, J. Malick, 2012, Mathematical Programming.

Numerical Study of Semidefinite Bounds for the k-cluster Problem

Frédéric Roupin, Jérôme Malick, J. Malick, 2010, Electron. Notes Discret. Math..

Local linear convergence of alternating and averaged nonconvex projections

A. Lewis, J. Malick, D. R. Luke, 2015 .

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

Jean-Baptiste Hiriart-Urruty, Jérôme Malick, J. Hiriart-Urruty, 2012, J. Optim. Theory Appl..

Chance constrained problems: a bilevel convex optimization perspective

Yassine Laguel, J'erome Malick, Wim Ackooij, 2021, 2103.10832.

Newton Methods for Nonsmooth Convex Minimization : Connections between U-Lagrangian , Riemannian Newton and SQP

J. Malick, Scott A. Miller, 2004 .

A smoothing approach for composite conditional gradient with nonsmooth loss

J. Malick, F. Pierucci, Zaïd Harchaoui, 2014 .

Cut-Generating Functions and S-Free Sets

Gérard Cornuéjols, Jérôme Malick, Michele Conforti, 2015, Math. Oper. Res..

Large-scale image classification with trace-norm regularization

Miroslav Dudík, J. Malick, Mattis Paulin, 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.

SDLS: a Matlab package for solving conic least-squares problems

Didier Henrion, Jerome Malick, J. Malick, 2007, 0709.2556.

Second-order differentiability of probability functions

J. Malick, W. van Ackooij, 2016, Optimization Letters.