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ORCIDCristóbal Guzmán
Person information
- affiliation: University of Twente, Department of Applied Mathematics, Enschede, The Netherlands
- affiliation: Centrum Wiskunde & Informatica, Amsterdam, The Netherlands
- affiliation (PhD): Georgia Tech, Atlanta, GA, USA
- affiliation: University of Chile, Mathematical Engineering Department, Santiago, Chile
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2020 – today
- 2026
[j17]Jelena Diakonikolas
, Cristóbal Guzmán:
Optimization on a Finer Scale: Bounded Local Subgradient Variation Perspective. SIAM J. Optim. 36(1): 152-184 (2026)- [j16]Tomás González, Cristóbal Guzmán, Courtney Paquette:
Mirror Descent Algorithms with Nearly Dimension-Independent Rates for Differentially-Private Stochastic Saddle-Point Problems. SIAM J. Optim. 36(1): 233-262 (2026) - [i32]Badih Ghazi, Cristóbal Guzmán, Pritish Kamath, Alexander Knop, Ravi Kumar, Pasin Manurangsi:
Computational Hardness of Private Coreset. CoRR abs/2602.17488 (2026) - 2025
- [j15]Mario Bravo, Juan P. Flores-Mella, Cristóbal Guzmán:
Mixing Times and Privacy Analysis for the Projected Langevin Algorithm under a Modulus of Continuity. J. Mach. Learn. Res. 26: 304:1-304:33 (2025) - [c24]Juan Pablo Contreras, Cristóbal Guzmán, David Martínez-Rubio:
Non-Euclidean High-Order Smooth Convex Optimization Extended Abstract. COLT 2025: 1330 - [c23]Badih Ghazi, Cristóbal Guzmán, Pritish Kamath, Alexander Knop, Ravi Kumar, Pasin Manurangsi, Sushant Sachdeva:
PREM: Privately Answering Statistical Queries with Relative Error. COLT 2025: 2460 - [c22]Quan M. Nguyen, Nishant A. Mehta, Cristóbal Guzmán:
Beyond Minimax Rates in Group Distributionally Robust Optimization via a Novel Notion of Sparsity. ICML 2025 - [i31]Mario Bravo, Juan P. Flores-Mella, Cristóbal Guzmán:
Mixing Times and Privacy Analysis for the Projected Langevin Algorithm under a Modulus of Continuity. CoRR abs/2501.04134 (2025) - [i30]Badih Ghazi, Cristóbal Guzmán, Pritish Kamath, Alexander Knop, Ravi Kumar, Pasin Manurangsi, Sushant Sachdeva:
PREM: Privately Answering Statistical Queries with Relative Error. CoRR abs/2502.14809 (2025) - [i29]Natalia Ponomareva, Zheng Xu, H. Brendan McMahan, Peter Kairouz, Lucas Rosenblatt, Vincent Cohen-Addad, Cristóbal Guzmán, Ryan McKenna, Galen Andrew, Alex Bie, Da Yu, Alex Kurakin, Morteza Zadimoghaddam, Sergei Vassilvitskii, Andreas Terzis:
How to DP-fy Your Data: A Practical Guide to Generating Synthetic Data With Differential Privacy. CoRR abs/2512.03238 (2025) - 2024
- [j14]Digvijay Boob, Cristóbal Guzmán:
Optimal algorithms for differentially private stochastic monotone variational inequalities and saddle-point problems. Math. Program. 204(1): 255-297 (2024) - [j13]Jelena Diakonikolas, Cristóbal Guzmán:
Complementary composite minimization, small gradients in general norms, and applications. Math. Program. 208(1): 319-363 (2024) - [j12]Alexandre d'Aspremont, Cristóbal Guzmán, Clément Lezane:
Optimal Algorithms for Stochastic Complementary Composite Minimization. SIAM J. Optim. 34(1): 163-189 (2024) - [j11]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): 5408-5409 (2024) - [c21]Michael Menart, Enayat Ullah, Raman Arora, Raef Bassily, Cristóbal Guzmán:
Differentially Private Non-Convex Optimization under the KL Condition with Optimal Rates. ALT 2024: 868-906 - [c20]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: 1982 - [c19]Raef Bassily, Cristóbal Guzmán, Michael Menart:
Private Algorithms for Stochastic Saddle Points and Variational Inequalities: Beyond Euclidean Geometry. NeurIPS 2024 - [c18]Badih Ghazi, Cristóbal Guzmán, Pritish Kamath, Ravi Kumar, Pasin Manurangsi:
Differentially Private Optimization with Sparse Gradients. NeurIPS 2024 - [c17]Enayat Ullah, Michael Menart, Raef Bassily, Cristóbal Guzmán, Raman Arora:
Public-data Assisted Private Stochastic Optimization: Power and Limitations. NeurIPS 2024 - [i28]Tomás González, Cristóbal Guzmán, Courtney Paquette:
Mirror Descent Algorithms with Nearly Dimension-Independent Rates for Differentially-Private Stochastic Saddle-Point Problems. CoRR abs/2403.02912 (2024) - [i27]Enayat Ullah, Michael Menart, Raef Bassily, Cristóbal Guzmán, Raman Arora:
Public-data Assisted Private Stochastic Optimization: Power and Limitations. CoRR abs/2403.03856 (2024) - [i26]Jelena Diakonikolas, Cristóbal Guzmán:
Optimization on a Finer Scale: Bounded Local Subgradient Variation Perspective. CoRR abs/2403.16317 (2024) - [i25]Badih Ghazi, Cristóbal Guzmán, Pritish Kamath, Ravi Kumar, Pasin Manurangsi:
Differentially Private Optimization with Sparse Gradients. CoRR abs/2404.10881 (2024) - [i24]Hédi Hadiji, Sarah Sachs, Cristóbal Guzmán:
Tracking solutions of time-varying variational inequalities. CoRR abs/2406.14059 (2024) - [i23]Quan Nguyen, Nishant A. Mehta, Cristóbal Guzmán:
Beyond Minimax Rates in Group Distributionally Robust Optimization via a Novel Notion of Sparsity. CoRR abs/2410.00690 (2024) - [i22]Raef Bassily, Cristóbal Guzmán, Michael Menart:
Private Algorithms for Stochastic Saddle Points and Variational Inequalities: Beyond Euclidean Geometry. CoRR abs/2411.05198 (2024) - [i21]Juan Pablo Contreras, Cristóbal Guzmán, David Martínez-Rubio:
Non-Euclidean High-Order Smooth Convex Optimization. CoRR abs/2411.08987 (2024) - 2023
- [c16]Raef Bassily, Cristóbal Guzmán, Michael Menart:
Differentially Private Algorithms for the Stochastic Saddle Point Problem with Optimal Rates for the Strong Gap. COLT 2023: 2482-2508 - [c15]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: 1060-1092 - [i20]Raef Bassily, Cristóbal Guzmán, Michael Menart:
Differentially Private Algorithms for the Stochastic Saddle Point Problem with Optimal Rates for the Strong Gap. CoRR abs/2302.12909 (2023) - [i19]Michael Menart, Enayat Ullah, Raman Arora, Raef Bassily, Cristóbal Guzmán:
Differentially Private Non-Convex Optimization under the KL Condition with Optimal Rates. CoRR abs/2311.13447 (2023) - 2022
- [j10]Cristóbal Guzmán, Javiera Riffo, Claudio Telha, Mathieu Van Vyve:
A sequential Stackelberg game for dynamic inspection problems. Eur. J. Oper. Res. 302(2): 727-739 (2022) - [j9]José Correa, Cristóbal Guzmán, Thanasis Lianeas, Evdokia Nikolova, Marc Schröder:
Network Pricing: How to Induce Optimal Flows Under Strategic Link Operators. Oper. Res. 70(1): 472-489 (2022) - [c14]Raman Arora, Raef Bassily, Cristóbal Guzmán, Michael Menart, Enayat Ullah:
Differentially Private Generalized Linear Models Revisited. NeurIPS 2022 - [c13]Xufeng Cai, Chaobing Song, Cristóbal Guzmán, Jelena Diakonikolas:
Stochastic Halpern Iteration with Variance Reduction for Stochastic Monotone Inclusions. NeurIPS 2022 - [c12]Sarah Sachs, Hédi Hadiji, Tim van Erven, Cristóbal Guzmán:
Between Stochastic and Adversarial Online Convex Optimization: Improved Regret Bounds via Smoothness. NeurIPS 2022 - [i18]Sarah Sachs, Hédi Hadiji, Tim van Erven, Cristóbal Guzmán:
Between Stochastic and Adversarial Online Convex Optimization: Improved Regret Bounds via Smoothness. CoRR abs/2202.07554 (2022) - [i17]Xufeng Cai, Chaobing Song, Cristóbal Guzmán, Jelena Diakonikolas:
A Stochastic Halpern Iteration with Variance Reduction for Stochastic Monotone Inclusion Problems. CoRR abs/2203.09436 (2022) - [i16]Raman Arora, Raef Bassily, Cristóbal Guzmán, Michael Menart, Enayat Ullah:
Differentially Private Generalized Linear Models Revisited. CoRR abs/2205.03014 (2022) - [i15]Raman Arora, Raef Bassily, Tomás González, Cristóbal Guzmán, Michael Menart, Enayat Ullah:
Faster Rates of Convergence to Stationary Points in Differentially Private Optimization. CoRR abs/2206.00846 (2022) - [i14]Alexandre d'Aspremont, Cristóbal Guzmán, Clément Lezane:
Optimal Algorithms for Stochastic Complementary Composite Minimization. CoRR abs/2211.01758 (2022) - 2021
- [j8]Vitaly Feldman, Cristóbal Guzmán, Santosh Srinivas Vempala:
Statistical Query Algorithms for Mean Vector Estimation and Stochastic Convex Optimization. Math. Oper. Res. 46(3): 912-945 (2021) - [j7]Santiago Armstrong, Cristóbal Guzmán, Carlos A. Sing-Long:
An Optimal Algorithm for Strict Circular Seriation. SIAM J. Math. Data Sci. 3(4): 1223-1250 (2021) - [c11]Raef Bassily, Cristóbal Guzmán, Anupama Nandi:
Non-Euclidean Differentially Private Stochastic Convex Optimization. COLT 2021: 474-499 - [c10]Raef Bassily, Cristóbal Guzmán, Michael Menart:
Differentially Private Stochastic Optimization: New Results in Convex and Non-Convex Settings. NeurIPS 2021: 9317-9329 - [c9]Cristóbal Guzmán, Nishant A. Mehta, Ali Mortazavi:
Best-case lower bounds in online learning. NeurIPS 2021: 21923-21934 - [c8]Siqi Zhang, Junchi Yang, Cristóbal Guzmán, Negar Kiyavash, Niao He:
The complexity of nonconvex-strongly-concave minimax optimization. UAI 2021: 482-492 - [i13]Jelena Diakonikolas, Cristóbal Guzmán:
Complementary Composite Minimization, Small Gradients in General Norms, and Applications to Regression Problems. CoRR abs/2101.11041 (2021) - [i12]Raef Bassily, Cristóbal Guzmán, Anupama Nandi:
Non-Euclidean Differentially Private Stochastic Convex Optimization. CoRR abs/2103.01278 (2021) - [i11]Siqi Zhang, Junchi Yang, Cristóbal Guzmán, Negar Kiyavash, Niao He:
The Complexity of Nonconvex-Strongly-Concave Minimax Optimization. CoRR abs/2103.15888 (2021) - [i10]Digvijay Boob, Cristóbal Guzmán:
Optimal Algorithms for Differentially Private Stochastic Monotone Variational Inequalities and Saddle-Point Problems. CoRR abs/2104.02988 (2021) - [i9]Santiago Armstrong, Cristóbal Guzmán, Carlos A. Sing-Long:
An Optimal Algorithm for Strict Circular Seriation. CoRR abs/2106.05944 (2021) - [i8]Cristóbal Guzmán, Nishant A. Mehta, Ali Mortazavi:
Best-Case Lower Bounds in Online Learning. CoRR abs/2106.12688 (2021) - [i7]Raef Bassily, Cristóbal Guzmán, Michael Menart:
Differentially Private Stochastic Optimization: New Results in Convex and Non-Convex Settings. CoRR abs/2107.05585 (2021) - 2020
- [j6]Jelena Diakonikolas, Cristóbal Guzmán:
Lower Bounds for Parallel and Randomized Convex Optimization. J. Mach. Learn. Res. 21: 5:1-5:31 (2020) - [c7]Raef Bassily, Vitaly Feldman, Cristóbal Guzmán, Kunal Talwar:
Stability of Stochastic Gradient Descent on Nonsmooth Convex Losses. NeurIPS 2020 - [i6]Raef Bassily, Vitaly Feldman, Cristóbal Guzmán, Kunal Talwar:
Stability of Stochastic Gradient Descent on Nonsmooth Convex Losses. CoRR abs/2006.06914 (2020)
2010 – 2019
- 2019
- [c6]Jelena Diakonikolas, Cristóbal Guzmán:
Lower Bounds for Parallel and Randomized Convex Optimization. COLT 2019: 1132-1157 - 2018
- [j5]Alexandre d'Aspremont, Cristóbal Guzmán, Martin Jaggi:
Optimal Affine-Invariant Smooth Minimization Algorithms. SIAM J. Optim. 28(3): 2384-2405 (2018) - [c5]José Correa, Cristóbal Guzmán, Thanasis Lianeas, Evdokia Nikolova, Marc Schröder:
Network Pricing: How to Induce Optimal Flows Under Strategic Link Operators. EC 2018: 375-392 - [c4]Daniel Dadush, Cristóbal Guzmán, Neil Olver:
Fast, Deterministic and Sparse Dimensionality Reduction. SODA 2018: 1330-1344 - [i5]Jelena Diakonikolas, Cristóbal Guzmán:
Lower Bounds for Parallel and Randomized Convex Optimization. CoRR abs/1811.01903 (2018) - 2017
- [j4]Maria Dostert, Cristóbal Guzmán, Fernando Mário de Oliveira Filho, Frank Vallentin:
New Upper Bounds for the Density of Translative Packings of Three-Dimensional Convex Bodies with Tetrahedral Symmetry. Discret. Comput. Geom. 58(2): 449-481 (2017) - [j3]Gábor Braun, Cristóbal Guzmán, Sebastian Pokutta:
Lower Bounds on the Oracle Complexity of Nonsmooth Convex Optimization via Information Theory. IEEE Trans. Inf. Theory 63(7): 4709-4724 (2017) - [c3]Vitaly Feldman, Cristóbal Guzmán, Santosh S. Vempala:
Statistical Query Algorithms for Mean Vector Estimation and Stochastic Convex Optimization. SODA 2017: 1265-1277 - 2015
- [b1]Cristóbal Guzmán:
Information, complexity and structure in convex optimization. Georgia Institute of Technology, Atlanta, GA, USA, 2015 - [j2]Cristóbal Guzmán, Arkadi Nemirovski:
On lower complexity bounds for large-scale smooth convex optimization. J. Complex. 31(1): 1-14 (2015) - [c2]Cristóbal Guzmán:
Open Problem: The Oracle Complexity of Smooth Convex Optimization in Nonstandard Settings. COLT 2015: 1761-1763 - [i4]Vitaly Feldman, Cristóbal Guzmán, Santosh S. Vempala:
Statistical Query Algorithms for Stochastic Convex Optimization. CoRR abs/1512.09170 (2015) - 2014
- [j1]Roberto Cominetti, Cristóbal Guzmán:
Network congestion control with Markovian multipath routing. Math. Program. 147(1-2): 231-251 (2014) - [i3]Gábor Braun, Cristóbal Guzmán, Sebastian Pokutta:
Lower Bounds on the Oracle Complexity of Nonsmooth Convex Optimization via Information Theory. CoRR abs/1407.5144 (2014) - 2013
- [i2]Cristóbal Guzmán, Arkadi Nemirovski:
On Lower Complexity Bounds for Large-Scale Smooth Convex Optimization. CoRR abs/1307.5001 (2013) - 2011
- [c1]Roberto Cominetti, Cristóbal Guzmán:
Network congestion control with Markovian multipath routing. NetGCoop 2011: 1-8 - [i1]Roberto Cominetti, Cristóbal Guzmán:
Network Congestion Control with Markovian Multipath Routing. CoRR abs/1107.2900 (2011)
Coauthor Index
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