Cristóbal Guzmán

20 papers · 2015–2025 · 5 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird 🌉 Interdisciplinary Bridge 🧭 Keyword Pioneer 🌍 Conference Polyglot (5) 🏃 Academic Marathon (10) 🐝 Cross-Pollinator (10) 🗺️ Taxonomy Completionist (22) 🏆 Keyword Champion (3) 🔬 Deep Specialist (11) 🔥 Unstoppable (7) 🗃️ Keyword Collector (67) 💎 Century Club (20) ⚡ Prolific Year (5)

Conferences

NIPS (9) COLT (7) JMLR (2) ALT (1) UAI (1)

Top co-authors

Raef Bassily (8) Michael Menart (6) Jelena Diakonikolas (3) Raman Arora (3) Enayat Ullah (3) Ravi Kumar (2) Pritish Kamath (2) Badih Ghazi (2) Pasin Manurangsi (2) Chaobing Song (1)

Research topics

Differential Privacy (3)

Keywords

differential privacy (10) stochastic optimization (6) convex optimization (4) stochastic gradient descent (3) oracle complexity (3) stochastic convex optimization (3) lower bound (3) dimension-independent rate (2) first-order method (2) excess population risk (2) generalized linear model (2) minimax optimization (2) non-convex optimization (2) gradient descent (2) online convex optimization (2) parallel algorithm (2) complexity bound (2) regret bound (2) randomized algorithm (2) sparse regression (1)

Papers

PREM: Privately Answering Statistical Queries with Relative Error COLT 2025

Mixing Times and Privacy Analysis for the Projected Langevin Algorithm under a Modulus of Continuity JMLR 2025

Non-Euclidean High-Order Smooth Convex Optimization Extended Abstract COLT 2025

Differentially Private Non-Convex Optimization under the KL Condition with Optimal Rates ALT 2024

Mirror Descent Algorithms with Nearly Dimension-Independent Rates for Differentially-Private Stochastic Saddle-Point Problems extended abstract COLT 2024

Public-data Assisted Private Stochastic Optimization: Power and Limitations NIPS 2024

Differentially Private Optimization with Sparse Gradients NIPS 2024

Private Algorithms for Stochastic Saddle Points and Variational Inequalities: Beyond Euclidean Geometry NIPS 2024

Differentially Private Algorithms for the Stochastic Saddle Point Problem with Optimal Rates for the Strong Gap COLT 2023

Between Stochastic and Adversarial Online Convex Optimization: Improved Regret Bounds via Smoothness NIPS 2022

Differentially Private Generalized Linear Models Revisited NIPS 2022

Stochastic Halpern Iteration with Variance Reduction for Stochastic Monotone Inclusions NIPS 2022

Non-Euclidean Differentially Private Stochastic Convex Optimization COLT 2021

The complexity of nonconvex-strongly-concave minimax optimization UAI 2021

Differentially Private Stochastic Optimization: New Results in Convex and Non-Convex Settings NIPS 2021

Best-case lower bounds in online learning NIPS 2021

Stability of Stochastic Gradient Descent on Nonsmooth Convex Losses NIPS 2020

Lower Bounds for Parallel and Randomized Convex Optimization JMLR 2020

Lower Bounds for Parallel and Randomized Convex Optimization COLT 2019

Open Problem: The Oracle Complexity of Smooth Convex Optimization in Nonstandard Settings COLT 2015