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Mateo Díaz
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2020 – today
- 2024
- [j7]Joshua Cutler, Mateo Díaz, Dmitriy Drusvyatskiy:
Stochastic Approximation with Decision-Dependent Distributions: Asymptotic Normality and Optimality. J. Mach. Learn. Res. 25: 90:1-90:49 (2024) - [j6]David L. Applegate, Mateo Díaz, Haihao Lu, Miles Lubin:
Infeasibility Detection with Primal-Dual Hybrid Gradient for Large-Scale Linear Programming. SIAM J. Optim. 34(1): 459-484 (2024) - [c4]Eitan Levin, Mateo Díaz:
Any-dimensional equivariant neural networks. AISTATS 2024: 2773-2781 - 2023
- [j5]Mateo Díaz, Benjamin Grimmer
:
Optimal Convergence Rates for the Proximal Bundle Method. SIAM J. Optim. 33(2): 424-454 (2023) - [i8]Mateo Díaz, Ethan N. Epperly, Zachary Frangella, Joel A. Tropp, Robert J. Webber:
Robust, randomized preconditioning for kernel ridge regression. CoRR abs/2304.12465 (2023) - [i7]Eitan Levin
Any-dimensional equivariant neural networks. CoRR abs/2306.06327 (2023) - 2022
- [j4]Qi Luo
Optimization of vaccination for COVID-19 in the midst of a pandemic. Networks Heterog. Media 17(3): 443-466 (2022) - [j3]Damek Davis, Mateo Díaz, Dmitriy Drusvyatskiy
Escaping Strict Saddle Points of the Moreau Envelope in Nonsmooth Optimization. SIAM J. Optim. 32(3): 1958-1983 (2022) - [i6]Joshua Cutler, Mateo Díaz, Dmitriy Drusvyatskiy:
Stochastic approximation with decision-dependent distributions: asymptotic normality and optimality. CoRR abs/2207.04173 (2022) - 2021
- [j2]Vasileios Charisopoulos
Low-Rank Matrix Recovery with Composite Optimization: Good Conditioning and Rapid Convergence. Found. Comput. Math. 21(6): 1505-1593 (2021) - [c3]David L. Applegate, Mateo Díaz, Oliver Hinder, Haihao Lu, Miles Lubin, Brendan O'Donoghue, Warren Schudy:
Practical Large-Scale Linear Programming using Primal-Dual Hybrid Gradient. NeurIPS 2021: 20243-20257 - [i5]Damek Davis, Mateo Díaz, Dmitriy Drusvyatskiy:
Escaping strict saddle points of the Moreau envelope in nonsmooth optimization. CoRR abs/2106.09815 (2021) - [i4]Damek Davis, Mateo Díaz, Kaizheng Wang:
Clustering a Mixture of Gaussians with Unknown Covariance. CoRR abs/2110.01602 (2021) - 2020
- [c2]Kaizheng Wang, Yuling Yan, Mateo Díaz:
Efficient Clustering for Stretched Mixtures: Landscape and Optimality. NeurIPS 2020 - [i3]Kaizheng Wang, Yuling Yan, Mateo Díaz:
Efficient Clustering for Stretched Mixtures: Landscape and Optimality. CoRR abs/2003.09960 (2020)
2010 – 2019
- 2019
- [j1]Mateo Díaz, Adolfo J. Quiroz
Local angles and dimension estimation from data on manifolds. J. Multivar. Anal. 173: 229-247 (2019) - [i2]Vasileios Charisopoulos, Damek Davis, Mateo Díaz, Dmitriy Drusvyatskiy:
Composite optimization for robust blind deconvolution. CoRR abs/1901.01624 (2019) - [i1]Vasileios Charisopoulos, Yudong Chen, Damek Davis, Mateo Díaz, Lijun Ding, Dmitriy Drusvyatskiy:
Low-rank matrix recovery with composite optimization: good conditioning and rapid convergence. CoRR abs/1904.10020 (2019) - 2017
- [c1]Mateo Díaz, Ronan Le Bras, Carla P. Gomes:
In Search of Balance: The Challenge of Generating Balanced Latin Rectangles. CPAIOR 2017: 68-76
Coauthor Index
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