Cristóbal Guzmán

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 45

Top Topics

Variance Reduction

Stackelberg Game

Differentially Private

Top Venues

Publications

Hédi Hadiji, Sarah Sachs, Cristóbal Guzmán
Tracking solutions of time-varying variational inequalities. CoRR (2024)
Michael Menart, Enayat Ullah, Raman Arora, Raef Bassily, Cristóbal Guzmán
Differentially Private Non-Convex Optimization under the KL Condition with Optimal Rates. ALT (2024)
Enayat Ullah, Michael Menart, Raef Bassily, Cristóbal Guzmán, Raman Arora
Public-data Assisted Private Stochastic Optimization: Power and Limitations. CoRR (2024)
Tomás González, Cristóbal Guzmán, Courtney Paquette
Mirror Descent Algorithms with Nearly Dimension-Independent Rates for Differentially-Private Stochastic Saddle-Point Problems extended abstract. COLT (2024)
Digvijay Boob, Cristóbal Guzmán
Optimal algorithms for differentially private stochastic monotone variational inequalities and saddle-point problems. Math. Program. 204 (1) (2024)
Tomás González, Cristóbal Guzmán, Courtney Paquette
Mirror Descent Algorithms with Nearly Dimension-Independent Rates for Differentially-Private Stochastic Saddle-Point Problems. CoRR (2024)
Jelena Diakonikolas, Cristóbal Guzmán
Optimization on a Finer Scale: Bounded Local Subgradient Variation Perspective. CoRR (2024)
Gábor Braun, Cristóbal Guzmán, Sebastian Pokutta
Corrections to "Lower Bounds on the Oracle Complexity of Nonsmooth Convex Optimization via Information Theory". IEEE Trans. Inf. Theory 70 (7) (2024)
Alexandre d'Aspremont, Cristóbal Guzmán, Clément Lezane
Optimal Algorithms for Stochastic Complementary Composite Minimization. SIAM J. Optim. 34 (1) (2024)
Badih Ghazi, Cristóbal Guzmán, Pritish Kamath, Ravi Kumar, Pasin Manurangsi
Differentially Private Optimization with Sparse Gradients. CoRR (2024)
Raef Bassily, Cristóbal Guzmán, Michael Menart
Differentially Private Algorithms for the Stochastic Saddle Point Problem with Optimal Rates for the Strong Gap. COLT (2023)
Raef Bassily, Cristóbal Guzmán, Michael Menart
Differentially Private Algorithms for the Stochastic Saddle Point Problem with Optimal Rates for the Strong Gap. CoRR (2023)
Raman Arora, Raef Bassily, Tomás González, Cristóbal Guzmán, Michael Menart, Enayat Ullah
Faster Rates of Convergence to Stationary Points in Differentially Private Optimization. ICML (2023)
Michael Menart, Enayat Ullah, Raman Arora, Raef Bassily, Cristóbal Guzmán
Differentially Private Non-Convex Optimization under the KL Condition with Optimal Rates. CoRR (2023)
Sarah Sachs, Hédi Hadiji, Tim van Erven, Cristóbal Guzmán
Accelerated Rates between Stochastic and Adversarial Online Convex Optimization. CoRR (2023)
Cristóbal Guzmán, Javiera Riffo, Claudio Telha, Mathieu Van Vyve
A sequential Stackelberg game for dynamic inspection problems. Eur. J. Oper. Res. 302 (2) (2022)
Raman Arora, Raef Bassily, Cristóbal Guzmán, Michael Menart, Enayat Ullah
Differentially Private Generalized Linear Models Revisited. CoRR (2022)
Sarah Sachs, Hédi Hadiji, Tim van Erven, Cristóbal Guzmán
Between Stochastic and Adversarial Online Convex Optimization: Improved Regret Bounds via Smoothness. NeurIPS (2022)
Raman Arora, Raef Bassily, Cristóbal Guzmán, Michael Menart, Enayat Ullah
Differentially Private Generalized Linear Models Revisited. NeurIPS (2022)
Sarah Sachs, Hédi Hadiji, Tim van Erven, Cristóbal Guzmán
Between Stochastic and Adversarial Online Convex Optimization: Improved Regret Bounds via Smoothness. CoRR (2022)
Raman Arora, Raef Bassily, Tomás González, Cristóbal Guzmán, Michael Menart, Enayat Ullah
Faster Rates of Convergence to Stationary Points in Differentially Private Optimization. CoRR (2022)
Xufeng Cai, Chaobing Song, Cristóbal Guzmán, Jelena Diakonikolas
Stochastic Halpern Iteration with Variance Reduction for Stochastic Monotone Inclusions. NeurIPS (2022)
Alexandre d'Aspremont, Cristóbal Guzmán, Clément Lezane
Optimal Algorithms for Stochastic Complementary Composite Minimization. CoRR (2022)
Xufeng Cai, Chaobing Song, Cristóbal Guzmán, Jelena Diakonikolas
A Stochastic Halpern Iteration with Variance Reduction for Stochastic Monotone Inclusion Problems. CoRR (2022)
José R. Correa, Cristóbal Guzmán, Thanasis Lianeas, Evdokia Nikolova, Marc Schröder
Network Pricing: How to Induce Optimal Flows Under Strategic Link Operators. Oper. Res. 70 (1) (2022)
Vitaly Feldman, Cristóbal Guzmán, Santosh Srinivas Vempala
Statistical Query Algorithms for Mean Vector Estimation and Stochastic Convex Optimization. Math. Oper. Res. 46 (3) (2021)
Jelena Diakonikolas, Cristóbal Guzmán
Complementary Composite Minimization, Small Gradients in General Norms, and Applications to Regression Problems. CoRR (2021)
Raef Bassily, Cristóbal Guzmán, Michael Menart
Differentially Private Stochastic Optimization: New Results in Convex and Non-Convex Settings. CoRR (2021)
Cristóbal Guzmán, Nishant A. Mehta, Ali Mortazavi
Best-Case Lower Bounds in Online Learning. CoRR (2021)
Santiago Armstrong, Cristóbal Guzmán, Carlos A. Sing-Long
An Optimal Algorithm for Strict Circular Seriation. SIAM J. Math. Data Sci. 3 (4) (2021)
Santiago Armstrong, Cristóbal Guzmán, Carlos A. Sing-Long
An Optimal Algorithm for Strict Circular Seriation. CoRR (2021)
Digvijay Boob, Cristóbal Guzmán
Optimal Algorithms for Differentially Private Stochastic Monotone Variational Inequalities and Saddle-Point Problems. CoRR (2021)
Siqi Zhang, Junchi Yang, Cristóbal Guzmán, Negar Kiyavash, Niao He
The Complexity of Nonconvex-Strongly-Concave Minimax Optimization. CoRR (2021)
Raef Bassily, Cristóbal Guzmán, Michael Menart
Differentially Private Stochastic Optimization: New Results in Convex and Non-Convex Settings. NeurIPS (2021)
Cristóbal Guzmán, Nishant A. Mehta, Ali Mortazavi
Best-case lower bounds in online learning. NeurIPS (2021)
Siqi Zhang, Junchi Yang, Cristóbal Guzmán, Negar Kiyavash, Niao He
The complexity of nonconvex-strongly-concave minimax optimization. UAI (2021)
Raef Bassily, Cristóbal Guzmán, Anupama Nandi
Non-Euclidean Differentially Private Stochastic Convex Optimization. CoRR (2021)
Jelena Diakonikolas, Cristóbal Guzmán
Lower Bounds for Parallel and Randomized Convex Optimization. J. Mach. Learn. Res. 21 (2020)
Raef Bassily, Vitaly Feldman, Cristóbal Guzmán, Kunal Talwar
Stability of Stochastic Gradient Descent on Nonsmooth Convex Losses. NeurIPS (2020)
Raef Bassily, Vitaly Feldman, Cristóbal Guzmán, Kunal Talwar
Stability of Stochastic Gradient Descent on Nonsmooth Convex Losses. CoRR (2020)
Jelena Diakonikolas, Cristóbal Guzmán
Lower Bounds for Parallel and Randomized Convex Optimization. COLT (2019)
Daniel Dadush, Cristóbal Guzmán, Neil Olver
Fast, Deterministic and Sparse Dimensionality Reduction. SODA (2018)
Alexandre d'Aspremont, Cristóbal Guzmán, Martin Jaggi
Optimal Affine-Invariant Smooth Minimization Algorithms. SIAM J. Optim. 28 (3) (2018)
Jelena Diakonikolas, Cristóbal Guzmán
Lower Bounds for Parallel and Randomized Convex Optimization. CoRR (2018)
José R. Correa, Cristóbal Guzmán, Thanasis Lianeas, Evdokia Nikolova, Marc Schröder
Network Pricing: How to Induce Optimal Flows Under Strategic Link Operators. EC (2018)