Network congestion control with Markovian multipath routing. - Roberto Cominetti; Cristóbal Guzmán (Math. Program., 2014)

Open Problem: The Oracle Complexity of Smooth Convex Optimization in Nonstandard Settings. - Cristóbal Guzmán (COLT, 2015)

Statistical Query Algorithms for Stochastic Convex Optimization. - Vitaly Feldman; Cristóbal Guzmán; Santosh S. Vempala (CoRR, 2015)

On lower complexity bounds for large-scale smooth convex optimization. - Cristóbal Guzmán; Arkadi Nemirovski (J. Complex., 2015)

Information, complexity and structure in convex optimization. - Cristóbal Guzmán (2015)

New Upper Bounds for the Density of Translative Packings of Three-Dimensional Convex Bodies with Tetrahedral Symmetry. - Maria Dostert; Cristóbal Guzmán; Fernando Mário de Oliveira Filho; Frank Vallentin (Discret. Comput. Geom., 2017)

Lower Bounds on the Oracle Complexity of Nonsmooth Convex Optimization via Information Theory. - Gábor Braun; Cristóbal Guzmán; Sebastian Pokutta (IEEE Trans. Inf. Theory, 2017)

Fast, Deterministic and Sparse Dimensionality Reduction. - Daniel Dadush; Cristóbal Guzmán; Neil Olver (SODA, 2018)

Optimal Affine-Invariant Smooth Minimization Algorithms. - Alexandre d'Aspremont; Cristóbal Guzmán; Martin Jaggi (SIAM J. Optim., 2018)

Stability of Stochastic Gradient Descent on Nonsmooth Convex Losses. - Raef Bassily; Vitaly Feldman; Cristóbal Guzmán; Kunal Talwar (NeurIPS, 2020)

Lower Bounds for Parallel and Randomized Convex Optimization. - Jelena Diakonikolas; Cristóbal Guzmán (J. Mach. Learn. Res., 2020)

Non-Euclidean Differentially Private Stochastic Convex Optimization. - Raef Bassily; Cristóbal Guzmán; Anupama Nandi (COLT, 2021)

Differentially Private Stochastic Optimization: New Results in Convex and Non-Convex Settings. - Raef Bassily; Cristóbal Guzmán; Michael Menart (NeurIPS, 2021)

Best-case lower bounds in online learning. - Cristóbal Guzmán; Nishant A. Mehta; Ali Mortazavi (NeurIPS, 2021)

The complexity of nonconvex-strongly-concave minimax optimization. - Siqi Zhang; Junchi Yang; Cristóbal Guzmán; Negar Kiyavash; Niao He (UAI, 2021)

Complementary Composite Minimization, Small Gradients in General Norms, and Applications to Regression Problems. - Jelena Diakonikolas; Cristóbal Guzmán (CoRR, 2021)

Statistical Query Algorithms for Mean Vector Estimation and Stochastic Convex Optimization. - Vitaly Feldman; Cristóbal Guzmán; Santosh Srinivas Vempala (Math. Oper. Res., 2021)

An Optimal Algorithm for Strict Circular Seriation. - Santiago Armstrong; Cristóbal Guzmán; Carlos A. Sing-Long (SIAM J. Math. Data Sci., 2021)

Differentially Private Generalized Linear Models Revisited. - Raman Arora; Raef Bassily; Cristóbal Guzmán; Michael Menart; Enayat Ullah (NeurIPS, 2022)

Stochastic Halpern Iteration with Variance Reduction for Stochastic Monotone Inclusions. - Xufeng Cai; Chaobing Song; Cristóbal Guzmán; Jelena Diakonikolas (NeurIPS, 2022)

Between Stochastic and Adversarial Online Convex Optimization: Improved Regret Bounds via Smoothness. - Sarah Sachs; Hédi Hadiji; Tim van Erven; Cristóbal Guzmán (NeurIPS, 2022)

A Stochastic Halpern Iteration with Variance Reduction for Stochastic Monotone Inclusion Problems. - Xufeng Cai; Chaobing Song; Cristóbal Guzmán; Jelena Diakonikolas (CoRR, 2022)

A sequential Stackelberg game for dynamic inspection problems. - Cristóbal Guzmán; Javiera Riffo; Claudio Telha; Mathieu Van Vyve (Eur. J. Oper. Res., 2022)

Network Pricing: How to Induce Optimal Flows Under Strategic Link Operators. - José Correa 001; Cristóbal Guzmán; Thanasis Lianeas; Evdokia Nikolova; Marc Schröder 002 (Oper. Res., 2022)

Differentially Private Algorithms for the Stochastic Saddle Point Problem with Optimal Rates for the Strong Gap. - Raef Bassily; Cristóbal Guzmán; Michael Menart (COLT, 2023)

Faster Rates of Convergence to Stationary Points in Differentially Private Optimization. - Raman Arora; Raef Bassily; Tomás González; Cristóbal Guzmán; Michael Menart; Enayat Ullah (ICML, 2023)

Accelerated Rates between Stochastic and Adversarial Online Convex Optimization. - Sarah Sachs; Hédi Hadiji; Tim van Erven; Cristóbal Guzmán (CoRR, 2023)

Differentially Private Non-Convex Optimization under the KL Condition with Optimal Rates. - Michael Menart; Enayat Ullah; Raman Arora; Raef Bassily; Cristóbal Guzmán (ALT, 2024)

Mirror Descent Algorithms with Nearly Dimension-Independent Rates for Differentially-Private Stochastic Saddle-Point Problems extended abstract. - Tomás González; Cristóbal Guzmán; Courtney Paquette (COLT, 2024)

Private Algorithms for Stochastic Saddle Points and Variational Inequalities: Beyond Euclidean Geometry. - Raef Bassily; Cristóbal Guzmán; Michael Menart (NeurIPS, 2024)

Differentially Private Optimization with Sparse Gradients. - Badih Ghazi; Cristóbal Guzmán; Pritish Kamath; Ravi Kumar 001; Pasin Manurangsi (NeurIPS, 2024)

Public-data Assisted Private Stochastic Optimization: Power and Limitations. - Enayat Ullah; Michael Menart; Raef Bassily; Cristóbal Guzmán; Raman Arora (NeurIPS, 2024)

Mirror Descent Algorithms with Nearly Dimension-Independent Rates for Differentially-Private Stochastic Saddle-Point Problems. - Tomás González; Cristóbal Guzmán; Courtney Paquette (CoRR, 2024)

Optimization on a Finer Scale: Bounded Local Subgradient Variation Perspective. - Jelena Diakonikolas; Cristóbal Guzmán (CoRR, 2024)

Tracking solutions of time-varying variational inequalities. - Hédi Hadiji; Sarah Sachs; Cristóbal Guzmán (CoRR, 2024)

Beyond Minimax Rates in Group Distributionally Robust Optimization via a Novel Notion of Sparsity. - Quan Nguyen; Nishant A. Mehta; Cristóbal Guzmán (CoRR, 2024)

Non-Euclidean High-Order Smooth Convex Optimization. - Juan Pablo Contreras; Cristóbal Guzmán; David Martínez-Rubio (CoRR, 2024)

Optimal algorithms for differentially private stochastic monotone variational inequalities and saddle-point problems. - Digvijay Boob; Cristóbal Guzmán (Math. Program., 2024)

Optimal Algorithms for Stochastic Complementary Composite Minimization. - Alexandre d'Aspremont; Cristóbal Guzmán; Clément Lezane (SIAM J. Optim., 2024)

Corrections to "Lower Bounds on the Oracle Complexity of Nonsmooth Convex Optimization via Information Theory". - Gábor Braun; Cristóbal Guzmán; Sebastian Pokutta (IEEE Trans. Inf. Theory, 2024)

Complementary composite minimization, small gradients in general norms, and applications. - Jelena Diakonikolas; Cristóbal Guzmán (Math. Program., 2024)

Non-Euclidean High-Order Smooth Convex Optimization Extended Abstract. - Juan Pablo Contreras; Cristóbal Guzmán; David Martínez-Rubio (COLT, 2025)

PREM: Privately Answering Statistical Queries with Relative Error. - Badih Ghazi; Cristóbal Guzmán; Pritish Kamath; Alexander Knop; Ravi Kumar 001; Pasin Manurangsi; Sushant Sachdeva (COLT, 2025)

Mixing Times and Privacy Analysis for the Projected Langevin Algorithm under a Modulus of Continuity. - Mario Bravo; Juan P. Flores-Mella; Cristóbal Guzmán (CoRR, 2025)