Mateo Díaz

According to our database, Mateo Díaz authored at least 17 papers between 2017 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2025

Preconditioned subgradient method for composite optimization: overparameterization and fast convergence.

Mateo Díaz, Liwei Jiang, Abdel Ghani Labassi

CoRR, September, 2025

Beyond Scores: Proximal Diffusion Models.

Zhenghan Fang, Mateo Díaz, Sam Buchanan, Jeremias Sulam

CoRR, July, 2025

On Transferring Transferability: Towards a Theory for Size Generalization.

Eitan Levin, Yuxin Ma, Mateo Díaz, Soledad Villar

CoRR, May, 2025

2024

Infeasibility Detection with Primal-Dual Hybrid Gradient for Large-Scale Linear Programming.

David L. Applegate, Mateo Díaz, Haihao Lu, Miles Lubin

SIAM J. Optim., March, 2024

Stochastic Approximation with Decision-Dependent Distributions: Asymptotic Normality and Optimality.

Joshua Cutler, Mateo Díaz, Dmitriy Drusvyatskiy

J. Mach. Learn. Res., 2024

Any-dimensional equivariant neural networks.

Eitan Levin, Mateo Díaz

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Optimal Convergence Rates for the Proximal Bundle Method.

Mateo Díaz, Benjamin Grimmer

SIAM J. Optim., 2023

Robust, randomized preconditioning for kernel ridge regression.

Mateo Díaz, Ethan N. Epperly, Zachary Frangella, Joel A. Tropp, Robert J. Webber

CoRR, 2023

2022

Escaping Strict Saddle Points of the Moreau Envelope in Nonsmooth Optimization.

Damek Davis, Mateo Díaz, Dmitriy Drusvyatskiy

SIAM J. Optim., September, 2022

Optimization of vaccination for COVID-19 in the midst of a pandemic.

Qi Luo, Ryan Weightman, Sean T. McQuade, Mateo Díaz, Emmanuel Trélat, William Barbour, Dan Work, Samitha Samaranayake, Benedetto Piccoli

Networks Heterog. Media, 2022

2021

Low-Rank Matrix Recovery with Composite Optimization: Good Conditioning and Rapid Convergence.

Vasileios Charisopoulos, Yudong Chen, Damek Davis, Mateo Díaz, Lijun Ding, Dmitriy Drusvyatskiy

Found. Comput. Math., 2021

Clustering a Mixture of Gaussians with Unknown Covariance.

Damek Davis, Mateo Díaz, Kaizheng Wang

CoRR, 2021

Practical Large-Scale Linear Programming using Primal-Dual Hybrid Gradient.

David L. Applegate, Mateo Díaz, Oliver Hinder, Haihao Lu, Miles Lubin, Brendan O'Donoghue, Warren Schudy

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Efficient Clustering for Stretched Mixtures: Landscape and Optimality.

Kaizheng Wang, Yuling Yan, Mateo Díaz

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

Local angles and dimension estimation from data on manifolds.

Mateo Díaz, Adolfo J. Quiroz, Mauricio Velasco

J. Multivar. Anal., 2019

Composite optimization for robust blind deconvolution.

Vasileios Charisopoulos, Damek Davis, Mateo Díaz, Dmitriy Drusvyatskiy

CoRR, 2019

2017

In Search of Balance: The Challenge of Generating Balanced Latin Rectangles.

Mateo Díaz, Ronan Le Bras, Carla P. Gomes

Proceedings of the Integration of AI and OR Techniques in Constraint Programming, 2017