Jérôme Malick

Publication Activity (10 Years)

Years Active: 2004-2024
Publications (10 Years): 50

Top Topics

Probability Functions

Top Venues

Publications

Yassine Laguel, Jérôme Malick, Wim van Ackooij
Chance-constrained programs with convex underlying functions: a bilevel convex optimization perspective. Comput. Optim. Appl. 88 (3) (2024)
Waïss Azizian, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos
What is the long-run distribution of stochastic gradient descent? A large deviations analysis. CoRR (2024)
Krishna Pillutla, Yassine Laguel, Jérôme Malick, Zaïd Harchaoui
Federated learning with superquantile aggregation for heterogeneous data. Mach. Learn. 113 (5) (2024)
Waïss Azizian, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos
The Rate of Convergence of Bregman Proximal Methods: Local Geometry Versus Regularity Versus Sharpness. SIAM J. Optim. 34 (3) (2024)
Waïss Azizian, Franck Iutzeler, Jérôme Malick
Exact Generalization Guarantees for (Regularized) Wasserstein Distributionally Robust Models. CoRR (2023)
Yu-Guan Hsieh, Yassine Laguel, Franck Iutzeler, Jérôme Malick
Push-Pull With Device Sampling. IEEE Trans. Autom. Control. 68 (12) (2023)
Gilles Bareilles, Franck Iutzeler, Jérôme Malick
Harnessing Structure in Composite Nonsmooth Minimization. SIAM J. Optim. 33 (3) (2023)
Gilles Bareilles, Franck Iutzeler, Jérôme Malick
Newton acceleration on manifolds identified by proximal gradient methods. Math. Program. 200 (1) (2023)
Waïss Azizian, Franck Iutzeler, Jérôme Malick
Exact Generalization Guarantees for (Regularized) Wasserstein Distributionally Robust Models. NeurIPS (2023)
Yu-Guan Hsieh, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos
Multi-Agent Online Optimization with Delays: Asynchronicity, Adaptivity, and Optimism. J. Mach. Learn. Res. 23 (2022)
Yassine Laguel, Jérôme Malick, Zaïd Harchaoui
Superquantile-Based Learning: A Direct Approach Using Gradient-Based Optimization. J. Signal Process. Syst. 94 (2) (2022)
Waïss Azizian, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos
On the rate of convergence of Bregman proximal methods in constrained variational inequalities. CoRR (2022)
Yu-Guan Hsieh, Yassine Laguel, Franck Iutzeler, Jérôme Malick
Push-Pull with Device Sampling. CoRR (2022)
Yu-Guan Hsieh, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos
Optimization in Open Networks via Dual Averaging. CDC (2021)
Dmitry Grishchenko, Franck Iutzeler, Jérôme Malick, Massih-Reza Amini
Distributed Learning with Sparse Communications by Identification. SIAM J. Math. Data Sci. 3 (2) (2021)
Yassine Laguel, Krishna Pillutla, Jérôme Malick, Zaïd Harchaoui
A Superquantile Approach to Federated Learning with Heterogeneous Devices. CISS (2021)
Dmitry Grishchenko, Franck Iutzeler, Jérôme Malick
Proximal Gradient Methods with Adaptive Subspace Sampling. Math. Oper. Res. 46 (4) (2021)
Waïss Azizian, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos
The Last-Iterate Convergence Rate of Optimistic Mirror Descent in Stochastic Variational Inequalities. COLT (2021)
Krishna Pillutla, Yassine Laguel, Jérôme Malick, Zaïd Harchaoui
Federated Learning with Heterogeneous Data: A Superquantile Optimization Approach. CoRR (2021)
Yu-Guan Hsieh, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos
Optimization in Open Networks via Dual Averaging. CoRR (2021)
Waïss Azizian, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos
The Last-Iterate Convergence Rate of Optimistic Mirror Descent in Stochastic Variational Inequalities. CoRR (2021)
Gilles Bareilles, Yassine Laguel, Dmitry Grishchenko, Franck Iutzeler, Jérôme Malick
Randomized Progressive Hedging methods for Multi-stage Stochastic Programming. CoRR (2020)
Yu-Guan Hsieh, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos
Multi-Agent Online Optimization with Delays: Asynchronicity, Adaptivity, and Optimism. CoRR (2020)
Yassine Laguel, Jérôme Malick, Zaïd Harchaoui
First-Order Optimization for Superquantile-Based Supervised Learning. MLSP (2020)
Yassine Laguel, Jérôme Malick, Zaïd Harchaoui
First-order Optimization for Superquantile-based Supervised Learning. CoRR (2020)
Konstantin Mishchenko, Franck Iutzeler, Jérôme Malick
A Distributed Flexible Delay-Tolerant Proximal Gradient Algorithm. SIAM J. Optim. 30 (1) (2020)
Yu-Guan Hsieh, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos
Explore Aggressively, Update Conservatively: Stochastic Extragradient Methods with Variable Stepsize Scaling. CoRR (2020)
Gilles Bareilles, Yassine Laguel, Dmitry Grishchenko, Franck Iutzeler, Jérôme Malick
Randomized Progressive Hedging methods for multi-stage stochastic programming. Ann. Oper. Res. 295 (2) (2020)
Franck Iutzeler, Jérôme Malick, Welington de Oliveira
Asynchronous level bundle methods. Math. Program. 184 (1) (2020)
Florent Bouchard, Bijan Afsari, Jérôme Malick, Marco Congedo
Approximate Joint Diagonalization with Riemannian Optimization on the General Linear Group. SIAM J. Matrix Anal. Appl. 41 (1) (2020)
Yassine Laguel, Krishna Pillutla, Jérôme Malick, Zaïd Harchaoui
Device Heterogeneity in Federated Learning: A Superquantile Approach. CoRR (2020)
Yu-Guan Hsieh, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos
Explore Aggressively, Update Conservatively: Stochastic Extragradient Methods with Variable Stepsize Scaling. NeurIPS (2020)
Yu-Guan Hsieh, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos
On the convergence of single-call stochastic extra-gradient methods. NeurIPS (2019)
Yu-Guan Hsieh, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos
On the convergence of single-call stochastic extra-gradient methods. CoRR (2019)
Jalal Fadili, Guillaume Garrigos, Jérôme Malick, Gabriel Peyré
Model Consistency for Learning with Mirror-Stratifiable Regularizers. AISTATS (2019)
Wim van Ackooij, Jérôme Malick
Eventual convexity of probability constraints with elliptical distributions. Math. Program. 175 (1-2) (2019)
Franck Iutzeler, Jérôme Malick
On the Proximal Gradient Algorithm with Alternated Inertia. J. Optim. Theory Appl. 176 (3) (2018)
Jalal Fadili, Jérôme Malick, Gabriel Peyré
Sensitivity Analysis for Mirror-Stratifiable Convex Functions. SIAM J. Optim. 28 (4) (2018)
Dmitry Grishchenko, Franck Iutzeler, Jérôme Malick, Massih-Reza Amini
Asynchronous Distributed Learning with Sparse Communications and Identification. CoRR (2018)
Florent Bouchard, Jérôme Malick, Marco Congedo
Riemannian Optimization and Approximate Joint Diagonalization for Blind Source Separation. IEEE Trans. Signal Process. 66 (8) (2018)
Konstantin Mishchenko, Franck Iutzeler, Jérôme Malick, Massih-Reza Amini
A Delay-tolerant Proximal-Gradient Algorithm for Distributed Learning. ICML (2018)
Wim van Ackooij, Jérôme Malick
Second-order differentiability of probability functions. Optim. Lett. 11 (1) (2017)
Wim van Ackooij, Nicolas Lebbe, Jérôme Malick
Regularized decomposition of large scale block-structured robust optimization problems. Comput. Manag. Sci. 14 (3) (2017)
Jérôme Malick, Welington de Oliveira, Sofia Zaourar
Uncontrolled inexact information within bundle methods. EURO J. Comput. Optim. 5 (1-2) (2017)
Jalal Fadili, Jérôme Malick, Gabriel Peyré
Sensitivity Analysis for Mirror-Stratifiable Convex Functions. CoRR (2017)
Florent Bouchard, Jérôme Malick, Marco Congedo
Approximate Joint Diagonalization According to the Natural Riemannian Distance. LVA/ICA (2017)
Nathan Krislock, Jérôme Malick, Frédéric Roupin
BiqCrunch: A Semidefinite Branch-and-Bound Method for Solving Binary Quadratic Problems. ACM Trans. Math. Softw. 43 (4) (2017)
Wim van Ackooij, Jérôme Malick
Decomposition algorithm for large-scale two-stage unit-commitment. Ann. Oper. Res. 238 (1-2) (2016)
Nathan Krislock, Jérôme Malick, Frédéric Roupin
Computational results of a semidefinite branch-and-bound algorithm for k-cluster. Comput. Oper. Res. 66 (2016)
Florent Bouchard, Louis Korczowski, Jérôme Malick, Marco Congedo
Approximate joint diagonalization within the Riemannian geometry framework. EUSIPCO (2016)
Michele Conforti, Gérard Cornuéjols, Aris Daniilidis, Claude Lemaréchal, Jérôme Malick
-Free Sets. Math. Oper. Res. 40 (2) (2015)
Nathan Krislock, Jérôme Malick, Frédéric Roupin
Improved semidefinite bounding procedure for solving Max-Cut problems to optimality. Math. Program. 143 (1-2) (2014)
Michele Conforti, Gérard Cornuéjols, Aris Daniilidis, Claude Lemaréchal, Jérôme Malick
Cut-Generating Functions. IPCO (2013)
Jérôme Malick, Frédéric Roupin
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. 140 (1) (2013)
Sofia Zaourar, Jérôme Malick
Prices stabilization for inexact unit-commitment problems. Math. Methods Oper. Res. 78 (3) (2013)
Jean-Baptiste Hiriart-Urruty, Jérôme Malick
A Fresh Variational-Analysis Look at the Positive Semidefinite Matrices World. J. Optim. Theory Appl. 153 (3) (2012)
Miroslav Dudík, Zaïd Harchaoui, Jérôme Malick
Lifted coordinate descent for learning with trace-norm regularization. AISTATS (2012)
Zaïd Harchaoui, Matthijs Douze, Mattis Paulin, Miroslav Dudík, Jérôme Malick
Large-scale image classification with trace-norm regularization. CVPR (2012)
Pierre-Antoine Absil, Jérôme Malick
Projection-like Retractions on Matrix Manifolds. SIAM J. Optim. 22 (1) (2012)
Marc Fuentes, Jérôme Malick, Claude Lemaréchal
Descentwise inexact proximal algorithms for smooth optimization. Comput. Optim. Appl. 53 (3) (2012)
Jérôme Malick, Frédéric Roupin
Solving k-cluster problems to optimality with semidefinite programming. Math. Program. 136 (2) (2012)
Didier Henrion, Jérôme Malick
Projection methods for conic feasibility problems: applications to polynomial sum-of-squares decompositions. Optim. Methods Softw. 26 (1) (2011)
Jérôme Malick, Frédéric Roupin
Numerical Study of Semidefinite Bounds for the k-cluster Problem. Electron. Notes Discret. Math. 36 (2010)
Jérôme Malick, Janez Povh, Franz Rendl, Angelika Wiegele
Regularization Methods for Semidefinite Programming. SIAM J. Optim. 20 (1) (2009)
Adrian S. Lewis, D. Russell Luke, Jérôme Malick
Local Linear Convergence for Alternating and Averaged Nonconvex Projections. Found. Comput. Math. 9 (4) (2009)
Adrian S. Lewis, Jérôme Malick
Alternating Projections on Manifolds. Math. Oper. Res. 33 (1) (2008)
Jérôme Malick
The spherical constraint in Boolean quadratic programs. J. Glob. Optim. 39 (4) (2007)
Scott A. Miller, Jérôme Malick
Newton methods for nonsmooth convex minimization: connections among U-Lagrangian, Riemannian Newton and SQP methods. Math. Program. 104 (2-3) (2005)
Jérôme Malick
A Dual Approach to Semidefinite Least-Squares Problems. SIAM J. Matrix Anal. Appl. 26 (1) (2004)