Mateo Díaz

23 papers A* 2A 1B 1Journal 19
YearRankTypeTitle / Venue / Authors
2026 J jnl
μpscaling small models: Principled warm starts and hyperparameter transfer.
CoRR
Yuxin Ma, Nan Chen, Mateo Díaz, Soufiane Hayou, Dmitriy Kunisky, Soledad Villar
2025 J jnl
Beyond Scores: Proximal Diffusion Models.
CoRR
Zhenghan Fang, Mateo Díaz, Sam Buchanan, Jeremias Sulam
2025 J jnl
On Transferring Transferability: Towards a Theory for Size Generalization.
CoRR
Eitan Levin, Yuxin Ma, Mateo Díaz, Soledad Villar
2025 J jnl
Preconditioned subgradient method for composite optimization: overparameterization and fast convergence.
CoRR
Mateo Díaz, Liwei Jiang, Abdel Ghani Labassi
2024 A conf
Any-dimensional equivariant neural networks.
AISTATS
Eitan Levin, Mateo Díaz
2024 J jnl
Infeasibility Detection with Primal-Dual Hybrid Gradient for Large-Scale Linear Programming.
SIAM J. Optim.
David L. Applegate, Mateo Díaz, Haihao Lu, Miles Lubin
2024 J jnl
Stochastic Approximation with Decision-Dependent Distributions: Asymptotic Normality and Optimality.
J. Mach. Learn. Res.
Joshua Cutler, Mateo Díaz, Dmitriy Drusvyatskiy
2023 J jnl
Any-dimensional equivariant neural networks.
CoRR
Eitan Levin, Mateo Díaz
2023 J jnl
Optimal Convergence Rates for the Proximal Bundle Method.
SIAM J. Optim.
Mateo Díaz, Benjamin Grimmer
2023 J jnl
Robust, randomized preconditioning for kernel ridge regression.
CoRR
Mateo Díaz, Ethan N. Epperly, Zachary Frangella, Joel A. Tropp, Robert J. Webber
2022 J jnl
Escaping Strict Saddle Points of the Moreau Envelope in Nonsmooth Optimization.
SIAM J. Optim.
Damek Davis, Mateo Díaz, Dmitriy Drusvyatskiy
2022 J jnl
Optimization of vaccination for COVID-19 in the midst of a pandemic.
Networks Heterog. Media
Qi Luo, Ryan Weightman, Sean T. McQuade, Mateo Díaz, Emmanuel Trélat, William Barbour, Dan Work, Samitha Samaranayake, Benedetto Piccoli
2022 J jnl
Stochastic approximation with decision-dependent distributions: asymptotic normality and optimality.
CoRR
Joshua Cutler, Mateo Díaz, Dmitriy Drusvyatskiy
2021 J jnl
Clustering a Mixture of Gaussians with Unknown Covariance.
CoRR
Damek Davis, Mateo Díaz, Kaizheng Wang
2021 J jnl
Escaping strict saddle points of the Moreau envelope in nonsmooth optimization.
CoRR
Damek Davis, Mateo Díaz, Dmitriy Drusvyatskiy
2021 J jnl
Low-Rank Matrix Recovery with Composite Optimization: Good Conditioning and Rapid Convergence.
Found. Comput. Math.
Vasileios Charisopoulos, Yudong Chen, Damek Davis, Mateo Díaz, Lijun Ding, Dmitriy Drusvyatskiy
2021 A* conf
Practical Large-Scale Linear Programming using Primal-Dual Hybrid Gradient.
NeurIPS
David L. Applegate, Mateo Díaz, Oliver Hinder, Haihao Lu, Miles Lubin, Brendan O'Donoghue, Warren Schudy
2020 A* conf
Efficient Clustering for Stretched Mixtures: Landscape and Optimality.
NeurIPS
Kaizheng Wang, Yuling Yan, Mateo Díaz
2020 J jnl
Efficient Clustering for Stretched Mixtures: Landscape and Optimality.
CoRR
Kaizheng Wang, Yuling Yan, Mateo Díaz
2019 J jnl
Composite optimization for robust blind deconvolution.
CoRR
Vasileios Charisopoulos, Damek Davis, Mateo Díaz, Dmitriy Drusvyatskiy
2019 J jnl
Local angles and dimension estimation from data on manifolds.
J. Multivar. Anal.
Mateo Díaz, Adolfo J. Quiroz, Mauricio Velasco
2019 J jnl
Low-rank matrix recovery with composite optimization: good conditioning and rapid convergence.
CoRR
Vasileios Charisopoulos, Yudong Chen, Damek Davis, Mateo Díaz, Lijun Ding, Dmitriy Drusvyatskiy
2017 B conf
In Search of Balance: The Challenge of Generating Balanced Latin Rectangles.
CPAIOR
Mateo Díaz, Ronan Le Bras, Carla P. Gomes