Jérôme Malick
Orcid: 0000-0003-0371-0457
According to our database1,
Jérôme Malick
authored at least 61 papers
between 2004 and 2024.
Collaborative distances:
Collaborative distances:
Timeline
Legend:
Book In proceedings Article PhD thesis Dataset OtherLinks
On csauthors.net:
Bibliography
2024
Chance-constrained programs with convex underlying functions: a bilevel convex optimization perspective.
Comput. Optim. Appl., July, 2024
Mach. Learn., May, 2024
The Rate of Convergence of Bregman Proximal Methods: Local Geometry Versus Regularity Versus Sharpness.
SIAM J. Optim., 2024
CoRR, 2024
What is the Long-Run Distribution of Stochastic Gradient Descent? A Large Deviations Analysis.
Proceedings of the Forty-first International Conference on Machine Learning, 2024
2023
SIAM J. Optim., September, 2023
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
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
SIAM J. Math. Data Sci., 2021
CoRR, 2021
The Last-Iterate Convergence Rate of Optimistic Mirror Descent in Stochastic Variational Inequalities.
Proceedings of the Conference on Learning Theory, 2021
Proceedings of the 55th Annual Conference on Information Sciences and Systems, 2021
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
SIAM J. Optim., 2020
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
Proceedings of the 30th IEEE International Workshop on Machine Learning for Signal Processing, 2020
2019
Math. Program., 2019
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
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
J. Optim. Theory Appl., 2018
CoRR, 2018
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
Regularized decomposition of large scale block-structured robust optimization problems.
Comput. Manag. Sci., 2017
Proceedings of the Latent Variable Analysis and Signal Separation, 2017
Variational-analysis look at combinatorial optimization, and other selected topics in optimization.
, 2017
2016
Comput. Oper. Res., 2016
Ann. Oper. Res., 2016
Proceedings of the 24th European Signal Processing Conference, 2016
2015
2014
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
Math. Methods Oper. Res., 2013
Proceedings of the Integer Programming and Combinatorial Optimization, 2013
2012
Math. Program., 2012
J. Optim. Theory Appl., 2012
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012
Comput. Optim. Appl., 2012
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
Electron. Notes Discret. Math., 2010
2009
Found. Comput. Math., 2009
2008
2007
2005
Newton methods for nonsmooth convex minimization: connections among U-Lagrangian, Riemannian Newton and SQP methods.
Math. Program., 2005
2004
SIAM J. Matrix Anal. Appl., 2004