Cristóbal Guzmán

Orcid: 0000-0002-1498-2055

Affiliations:
  • University of Twente, Department of Applied Mathematics, Enschede, The Netherlands
  • Centrum Wiskunde & Informatica, Amsterdam, The Netherlands
  • Georgia Tech, Atlanta, GA, USA (PhD)
  • University of Chile, Mathematical Engineering Department, Santiago, Chile


According to our database1, Cristóbal Guzmán authored at least 32 papers between 2014 and 2024.

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Bibliography

2024
Optimal Algorithms for Stochastic Complementary Composite Minimization.
SIAM J. Optim., March, 2024

Optimal algorithms for differentially private stochastic monotone variational inequalities and saddle-point problems.
Math. Program., March, 2024

Optimization on a Finer Scale: Bounded Local Subgradient Variation Perspective.
CoRR, 2024

Public-data Assisted Private Stochastic Optimization: Power and Limitations.
CoRR, 2024

Mirror Descent Algorithms with Nearly Dimension-Independent Rates for Differentially-Private Stochastic Saddle-Point Problems.
CoRR, 2024

2023
Differentially Private Non-Convex Optimization under the KL Condition with Optimal Rates.
CoRR, 2023

Accelerated Rates between Stochastic and Adversarial Online Convex Optimization.
CoRR, 2023

Faster Rates of Convergence to Stationary Points in Differentially Private Optimization.
Proceedings of the International Conference on Machine Learning, 2023

Differentially Private Algorithms for the Stochastic Saddle Point Problem with Optimal Rates for the Strong Gap.
Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

2022
Network Pricing: How to Induce Optimal Flows Under Strategic Link Operators.
Oper. Res., 2022

A sequential Stackelberg game for dynamic inspection problems.
Eur. J. Oper. Res., 2022

A Stochastic Halpern Iteration with Variance Reduction for Stochastic Monotone Inclusion Problems.
CoRR, 2022

Between Stochastic and Adversarial Online Convex Optimization: Improved Regret Bounds via Smoothness.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Stochastic Halpern Iteration with Variance Reduction for Stochastic Monotone Inclusions.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Differentially Private Generalized Linear Models Revisited.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021
An Optimal Algorithm for Strict Circular Seriation.
SIAM J. Math. Data Sci., 2021

Statistical Query Algorithms for Mean Vector Estimation and Stochastic Convex Optimization.
Math. Oper. Res., 2021

Complementary Composite Minimization, Small Gradients in General Norms, and Applications to Regression Problems.
CoRR, 2021

The complexity of nonconvex-strongly-concave minimax optimization.
Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

Best-case lower bounds in online learning.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Differentially Private Stochastic Optimization: New Results in Convex and Non-Convex Settings.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Non-Euclidean Differentially Private Stochastic Convex Optimization.
Proceedings of the Conference on Learning Theory, 2021

2020
Lower Bounds for Parallel and Randomized Convex Optimization.
J. Mach. Learn. Res., 2020

Stability of Stochastic Gradient Descent on Nonsmooth Convex Losses.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2018
Optimal Affine-Invariant Smooth Minimization Algorithms.
SIAM J. Optim., 2018

Fast, Deterministic and Sparse Dimensionality Reduction.
Proceedings of the Twenty-Ninth Annual ACM-SIAM Symposium on Discrete Algorithms, 2018

2017
Lower Bounds on the Oracle Complexity of Nonsmooth Convex Optimization via Information Theory.
IEEE Trans. Inf. Theory, 2017

New Upper Bounds for the Density of Translative Packings of Three-Dimensional Convex Bodies with Tetrahedral Symmetry.
Discret. Comput. Geom., 2017

2015
On lower complexity bounds for large-scale smooth convex optimization.
J. Complex., 2015

Statistical Query Algorithms for Stochastic Convex Optimization.
CoRR, 2015

Open Problem: The Oracle Complexity of Smooth Convex Optimization in Nonstandard Settings.
Proceedings of The 28th Conference on Learning Theory, 2015

2014
Network congestion control with Markovian multipath routing.
Math. Program., 2014


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