Mateo Díaz
Mateo Díaz
Johns Hopkins University
Verified email at - Homepage
Cited by
Cited by
Low-rank matrix recovery with composite optimization: good conditioning and rapid convergence
V Charisopoulos, Y Chen, D Davis, M Díaz, L Ding, D Drusvyatskiy
Foundations of Computational Mathematics 21 (6), 1505-1593, 2021
Practical large-scale linear programming using primal-dual hybrid gradient
D Applegate, M Díaz, O Hinder, H Lu, M Lubin, B O'Donoghue, W Schudy
Advances in Neural Information Processing Systems 34, 20243-20257, 2021
Composite optimization for robust rank one bilinear sensing
V Charisopoulos, D Davis, M Díaz, D Drusvyatskiy
Information and Inference: A Journal of the IMA 10 (2), 333-396, 2021
Optimal convergence rates for the proximal bundle method
M Díaz, B Grimmer
SIAM Journal on Optimization 33 (2), 424-454, 2023
Infeasibility detection with primal-dual hybrid gradient for large-scale linear programming
D Applegate, M Díaz, H Lu, M Lubin
SIAM Journal on Optimization 34 (1), 459-484, 2024
Clustering a mixture of gaussians with unknown covariance
D Davis, M Díaz, K Wang
arXiv preprint arXiv:2110.01602, 2021
Efficient clustering for stretched mixtures: Landscape and optimality
K Wang, Y Yan, M Díaz
Advances in Neural Information Processing Systems 33, 21309-21320, 2020
Local angles and dimension estimation from data on manifolds
M Díaz, AJ Quiroz, M Velasco
Journal of Multivariate Analysis 173, 229-247, 2019
The nonsmooth landscape of blind deconvolution
M Díaz
arXiv preprint arXiv:1911.08526, 2019
Compressed sensing of data with a known distribution
M Díaz, M Junca, F Rincón, M Velasco
Applied and Computational Harmonic Analysis 45 (3), 486-504, 2018
Escaping strict saddle points of the moreau envelope in nonsmooth optimization
D Davis, M Díaz, D Drusvyatskiy
SIAM Journal on Optimization 32 (3), 1958-1983, 2022
Stochastic approximation with decision-dependent distributions: asymptotic normality and optimality
J Cutler, M Díaz, D Drusvyatskiy
Journal of Machine Learning Research 25 (90), 1-49, 2024
Optimization of vaccination for COVID-19 in the midst of a pandemic
Q Luo, R Weightman, ST McQuade, M Díaz, E Trélat, W Barbour, D Work, ...
arXiv preprint arXiv:2203.09502, 2022
Robust, randomized preconditioning for kernel ridge regression
M Díaz, EN Epperly, Z Frangella, JA Tropp, RJ Webber
arXiv preprint arXiv:2304.12465, 2023
Any-dimensional equivariant neural networks
E Levin, M Díaz
International Conference on Artificial Intelligence and Statistics, 2773-2781, 2024
In Search of Balance: The Challenge of Generating Balanced Latin Rectangles
M Díaz, RL Bras, C Gomes
Integration of AI and OR Techniques in Constraint Programming: 14th …, 2017
The radius of statistical efficiency
J Cutler, M Díaz, D Drusvyatskiy
arXiv preprint arXiv:2405.09676, 2024
Controlling the False Discovery Rate in Subspace Selection
M Díaz, V Chandrasekaran
arXiv preprint arXiv:2404.09142, 2024
Complexity, Conditioning, and Saddle Avoidance in Nonsmooth Optimization
MD Diaz
Cornell University, 2021
Compressed sensing with an a priori distribution
M Díaz Díaz
Uniandes, 2016
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