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Jérôme Malick
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2020 – today
- 2024
- [j40]Yassine Laguel, Jérôme Malick, Wim van Ackooij:
Chance-constrained programs with convex underlying functions: a bilevel convex optimization perspective. Comput. Optim. Appl. 88(3): 819-847 (2024) - [j39]Krishna Pillutla, Yassine Laguel, Jérôme Malick, Zaïd Harchaoui:
Federated learning with superquantile aggregation for heterogeneous data. Mach. Learn. 113(5): 2955-3022 (2024) - [j38]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): 2440-2471 (2024) - [c15]Waïss Azizian, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos:
What is the Long-Run Distribution of Stochastic Gradient Descent? A Large Deviations Analysis. ICML 2024 - [i16]Waïss Azizian, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos:
What is the long-run distribution of stochastic gradient descent? A large deviations analysis. CoRR abs/2406.09241 (2024) - [i15]Florian Vincent, Waïss Azizian, Franck Iutzeler, Jérôme Malick:
skwdro: a library for Wasserstein distributionally robust machine learning. CoRR abs/2410.21231 (2024) - 2023
- [j37]Gilles Bareilles, Franck Iutzeler, Jérôme Malick:
Newton acceleration on manifolds identified by proximal gradient methods. Math. Program. 200(1): 37-70 (2023) - [j36]Gilles Bareilles, Franck Iutzeler, Jérôme Malick:
Harnessing Structure in Composite Nonsmooth Minimization. SIAM J. Optim. 33(3): 2222-2247 (2023) - [j35]Yu-Guan Hsieh, Yassine Laguel, Franck Iutzeler, Jérôme Malick:
Push-Pull With Device Sampling. IEEE Trans. Autom. Control. 68(12): 7179-7194 (2023) - [c14]Waïss Azizian, Franck Iutzeler, Jérôme Malick:
Exact Generalization Guarantees for (Regularized) Wasserstein Distributionally Robust Models. NeurIPS 2023 - [i14]Waïss Azizian, Franck Iutzeler, Jérôme Malick:
Exact Generalization Guarantees for (Regularized) Wasserstein Distributionally Robust Models. CoRR abs/2305.17076 (2023) - 2022
- [j34]Yu-Guan Hsieh, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos:
Multi-Agent Online Optimization with Delays: Asynchronicity, Adaptivity, and Optimism. J. Mach. Learn. Res. 23: 78:1-78:49 (2022) - [j33]Yassine Laguel, Jérôme Malick, Zaïd Harchaoui:
Superquantile-Based Learning: A Direct Approach Using Gradient-Based Optimization. J. Signal Process. Syst. 94(2): 161-177 (2022) - [i13]Yu-Guan Hsieh, Yassine Laguel, Franck Iutzeler, Jérôme Malick:
Push-Pull with Device Sampling. CoRR abs/2206.04113 (2022) - [i12]Waïss Azizian, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos:
On the rate of convergence of Bregman proximal methods in constrained variational inequalities. CoRR abs/2211.08043 (2022) - 2021
- [j32]Dmitry Grishchenko, Franck Iutzeler, Jérôme Malick:
Proximal Gradient Methods with Adaptive Subspace Sampling. Math. Oper. Res. 46(4): 1303-1323 (2021) - [j31]Dmitry Grishchenko, Franck Iutzeler, Jérôme Malick, Massih-Reza Amini:
Distributed Learning with Sparse Communications by Identification. SIAM J. Math. Data Sci. 3(2): 715-735 (2021) - [c13]Yu-Guan Hsieh, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos:
Optimization in Open Networks via Dual Averaging. CDC 2021: 514-520 - [c12]Yassine Laguel, Krishna Pillutla, Jérôme Malick, Zaïd Harchaoui:
A Superquantile Approach to Federated Learning with Heterogeneous Devices. CISS 2021: 1-6 - [c11]Waïss Azizian, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos:
The Last-Iterate Convergence Rate of Optimistic Mirror Descent in Stochastic Variational Inequalities. COLT 2021: 326-358 - [i11]Yu-Guan Hsieh, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos:
Optimization in Open Networks via Dual Averaging. CoRR abs/2105.13348 (2021) - [i10]Waïss Azizian, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos:
The Last-Iterate Convergence Rate of Optimistic Mirror Descent in Stochastic Variational Inequalities. CoRR abs/2107.01906 (2021) - [i9]Krishna Pillutla, Yassine Laguel, Jérôme Malick, Zaïd Harchaoui:
Federated Learning with Heterogeneous Data: A Superquantile Optimization Approach. CoRR abs/2112.09429 (2021) - 2020
- [j30]Gilles Bareilles, Yassine Laguel, Dmitry Grishchenko, Franck Iutzeler, Jérôme Malick:
Randomized Progressive Hedging methods for multi-stage stochastic programming. Ann. Oper. Res. 295(2): 535-560 (2020) - [j29]Franck Iutzeler, Jérôme Malick, Welington de Oliveira:
Asynchronous level bundle methods. Math. Program. 184(1): 319-348 (2020) - [j28]Konstantin Mishchenko, Franck Iutzeler, Jérôme Malick:
A Distributed Flexible Delay-Tolerant Proximal Gradient Algorithm. SIAM J. Optim. 30(1): 933-959 (2020) - [j27]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): 152-170 (2020) - [c10]Yassine Laguel, Jérôme Malick, Zaïd Harchaoui:
First-Order Optimization for Superquantile-Based Supervised Learning. MLSP 2020: 1-6 - [c9]Yu-Guan Hsieh, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos:
Explore Aggressively, Update Conservatively: Stochastic Extragradient Methods with Variable Stepsize Scaling. NeurIPS 2020 - [i8]Yassine Laguel, Krishna Pillutla, Jérôme Malick, Zaïd Harchaoui:
Device Heterogeneity in Federated Learning: A Superquantile Approach. CoRR abs/2002.11223 (2020) - [i7]Yu-Guan Hsieh, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos:
Explore Aggressively, Update Conservatively: Stochastic Extragradient Methods with Variable Stepsize Scaling. CoRR abs/2003.10162 (2020) - [i6]Gilles Bareilles, Yassine Laguel, Dmitry Grishchenko, Franck Iutzeler, Jérôme Malick:
Randomized Progressive Hedging methods for Multi-stage Stochastic Programming. CoRR abs/2009.12186 (2020) - [i5]Yassine Laguel, Jérôme Malick, Zaïd Harchaoui:
First-order Optimization for Superquantile-based Supervised Learning. CoRR abs/2009.14575 (2020) - [i4]Yu-Guan Hsieh, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos:
Multi-Agent Online Optimization with Delays: Asynchronicity, Adaptivity, and Optimism. CoRR abs/2012.11579 (2020)
2010 – 2019
- 2019
- [j26]Wim van Ackooij, Jérôme Malick:
Eventual convexity of probability constraints with elliptical distributions. Math. Program. 175(1-2): 1-27 (2019) - [c8]Jalal Fadili, Guillaume Garrigos, Jérôme Malick, Gabriel Peyré:
Model Consistency for Learning with Mirror-Stratifiable Regularizers. AISTATS 2019: 1236-1244 - [c7]Yu-Guan Hsieh, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos:
On the convergence of single-call stochastic extra-gradient methods. NeurIPS 2019: 6936-6946 - [i3]Yu-Guan Hsieh, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos:
On the convergence of single-call stochastic extra-gradient methods. CoRR abs/1908.08465 (2019) - 2018
- [j25]Franck Iutzeler, Jérôme Malick:
On the Proximal Gradient Algorithm with Alternated Inertia. J. Optim. Theory Appl. 176(3): 688-710 (2018) - [j24]Jalal Fadili, Jérôme Malick, Gabriel Peyré:
Sensitivity Analysis for Mirror-Stratifiable Convex Functions. SIAM J. Optim. 28(4): 2975-3000 (2018) - [j23]Florent Bouchard, Jérôme Malick, Marco Congedo:
Riemannian Optimization and Approximate Joint Diagonalization for Blind Source Separation. IEEE Trans. Signal Process. 66(8): 2041-2054 (2018) - [c6]Konstantin Mishchenko, Franck Iutzeler, Jérôme Malick, Massih-Reza Amini:
A Delay-tolerant Proximal-Gradient Algorithm for Distributed Learning. ICML 2018: 3584-3592 - [i2]Dmitry Grishchenko, Franck Iutzeler, Jérôme Malick, Massih-Reza Amini:
Asynchronous Distributed Learning with Sparse Communications and Identification. CoRR abs/1812.03871 (2018) - 2017
- [b1]Jérôme Malick:
Variational-analysis look at combinatorial optimization, and other selected topics in optimization. Grenoble Alpes University, France, 2017 - [j22]Wim van Ackooij, Nicolas Lebbe, Jérôme Malick:
Regularized decomposition of large scale block-structured robust optimization problems. Comput. Manag. Sci. 14(3): 393-421 (2017) - [j21]Jérôme Malick, Welington de Oliveira, Sofia Zaourar:
Uncontrolled inexact information within bundle methods. EURO J. Comput. Optim. 5(1-2): 5-29 (2017) - [j20]Wim van Ackooij, Jérôme Malick:
Second-order differentiability of probability functions. Optim. Lett. 11(1): 179-194 (2017) - [j19]Nathan Krislock, Jérôme Malick, Frédéric Roupin:
BiqCrunch: A Semidefinite Branch-and-Bound Method for Solving Binary Quadratic Problems. ACM Trans. Math. Softw. 43(4): 32:1-32:23 (2017) - [c5]Florent Bouchard, Jérôme Malick, Marco Congedo:
Approximate Joint Diagonalization According to the Natural Riemannian Distance. LVA/ICA 2017: 290-299 - [i1]Jalal Fadili, Jérôme Malick, Gabriel Peyré:
Sensitivity Analysis for Mirror-Stratifiable Convex Functions. CoRR abs/1707.03194 (2017) - 2016
- [j18]Wim van Ackooij, Jérôme Malick:
Decomposition algorithm for large-scale two-stage unit-commitment. Ann. Oper. Res. 238(1-2): 587-613 (2016) - [j17]Nathan Krislock, Jérôme Malick, Frédéric Roupin:
Computational results of a semidefinite branch-and-bound algorithm for k-cluster. Comput. Oper. Res. 66: 153-159 (2016) - [c4]Florent Bouchard, Louis Korczowski, Jérôme Malick, Marco Congedo:
Approximate joint diagonalization within the Riemannian geometry framework. EUSIPCO 2016: 210-214 - 2015
- [j16]Michele Conforti, Gérard Cornuéjols, Aris Daniilidis, Claude Lemaréchal, Jérôme Malick:
Cut-Generating Functions and S-Free Sets. Math. Oper. Res. 40(2): 276-391 (2015) - 2014
- [j15]Nathan Krislock, Jérôme Malick, Frédéric Roupin:
Improved semidefinite bounding procedure for solving Max-Cut problems to optimality. Math. Program. 143(1-2): 61-86 (2014) - 2013
- [j14]Sofia Zaourar, Jérôme Malick:
Prices stabilization for inexact unit-commitment problems. Math. Methods Oper. Res. 78(3): 341-359 (2013) - [j13]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): 99-124 (2013) - [c3]Michele Conforti, Gérard Cornuéjols, Aris Daniilidis, Claude Lemaréchal, Jérôme Malick:
Cut-Generating Functions. IPCO 2013: 123-132 - 2012
- [j12]Marc Fuentes, Jérôme Malick, Claude Lemaréchal:
Descentwise inexact proximal algorithms for smooth optimization. Comput. Optim. Appl. 53(3): 755-769 (2012) - [j11]Jean-Baptiste Hiriart-Urruty, Jérôme Malick:
A Fresh Variational-Analysis Look at the Positive Semidefinite Matrices World. J. Optim. Theory Appl. 153(3): 551-577 (2012) - [j10]Jérôme Malick, Frédéric Roupin:
Solving k-cluster problems to optimality with semidefinite programming. Math. Program. 136(2): 279-300 (2012) - [j9]Pierre-Antoine Absil, Jérôme Malick:
Projection-like Retractions on Matrix Manifolds. SIAM J. Optim. 22(1): 135-158 (2012) - [c2]Zaïd Harchaoui, Matthijs Douze, Mattis Paulin, Miroslav Dudík, Jérôme Malick:
Large-scale image classification with trace-norm regularization. CVPR 2012: 3386-3393 - [c1]Miroslav Dudík, Zaïd Harchaoui, Jérôme Malick:
Lifted coordinate descent for learning with trace-norm regularization. AISTATS 2012: 327-336 - 2011
- [j8]Didier Henrion, Jérôme Malick:
Projection methods for conic feasibility problems: applications to polynomial sum-of-squares decompositions. Optim. Methods Softw. 26(1): 23-46 (2011) - 2010
- [j7]Jérôme Malick, Frédéric Roupin:
Numerical Study of Semidefinite Bounds for the k-cluster Problem. Electron. Notes Discret. Math. 36: 399-406 (2010)
2000 – 2009
- 2009
- [j6]Adrian S. Lewis, D. Russell Luke, Jérôme Malick:
Local Linear Convergence for Alternating and Averaged Nonconvex Projections. Found. Comput. Math. 9(4): 485-513 (2009) - [j5]Jérôme Malick, Janez Povh, Franz Rendl, Angelika Wiegele:
Regularization Methods for Semidefinite Programming. SIAM J. Optim. 20(1): 336-356 (2009) - 2008
- [j4]Adrian S. Lewis, Jérôme Malick:
Alternating Projections on Manifolds. Math. Oper. Res. 33(1): 216-234 (2008) - 2007
- [j3]Jérôme Malick:
The spherical constraint in Boolean quadratic programs. J. Glob. Optim. 39(4): 609-622 (2007) - 2005
- [j2]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): 609-633 (2005) - 2004
- [j1]Jérôme Malick:
A Dual Approach to Semidefinite Least-Squares Problems. SIAM J. Matrix Anal. Appl. 26(1): 272-284 (2004)
Coauthor Index
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