← Authors

Blake Woodworth

14 papers · 2017–2025 · 5 conferences · across top CS/AI conferences

Achievements

🐝 Cross-Pollinator (4) 🐣 Hot Topic Early Bird 🌈 Renaissance Researcher (5) πŸ—ΊοΈ Taxonomy Completionist (20) πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (5) πŸƒ Academic Marathon (8) 🧭 Keyword Pioneer 🧬 Topic Evolution πŸ—ƒοΈ Keyword Collector (60) πŸ’Ž Century Club (14) πŸ”₯ Unstoppable (5) πŸ“ˆ Trend Setter ❓ The Questioner

Conferences

COLT (6) ICML (4) AISTATS (2) ICLR (1) IJCAI (1)

Top co-authors

Nathan Srebro (9) Ohad Shamir (3) Suriya Gunasekar (3) Karthik Sridharan (2) Michael Crawshaw (2) Francis Bach (2) Mingrui Liu (2) Brian Bullins (2) Mesrob I. Ohannessian (1) Dylan J. Foster (1)

Research topics

Statistics (1)

Keywords

convex optimization (3) gradient descent (2) oracle complexity (2) stochastic gradient descent (2) constrained optimization (1) natural gradient (1) non-convex optimization (1) distributed optimization (1) algorithmic fairness (1) computational complexity (1) fourier analysis (1) recursive regularization (1) natural gradient descent (1) statistical query (1) sample complexity (1) sample efficiency (1) linear regression (1) stochastic gradient (1) minimax complexity (1) federated learning (1)

Papers

Local Steps Speed Up Local GD for Heterogeneous Distributed Logistic Regression ICLR 2025
Constant Stepsize Local GD for Logistic Regression: Acceleration by Instability ICML 2025
Two Losses Are Better Than One: Faster Optimization Using a Cheaper Proxy ICML 2023
The Min-Max Complexity of Distributed Stochastic Convex Optimization with Intermittent Communication (Extended Abstract) IJCAI 2022
Non-Convex Optimization with Certificates and Fast Rates Through Kernel Sums of Squares COLT 2022
Mirrorless Mirror Descent: A Natural Derivation of Mirror Descent AISTATS 2021
Is Local SGD Better than Minibatch SGD? ICML 2020
The Gradient Complexity of Linear Regression COLT 2020
Kernel and Rich Regimes in Overparametrized Models COLT 2020
Guaranteed Validity for Empirical Approaches to Adaptive Data Analysis AISTATS 2020
Open Problem: The Oracle Complexity of Convex Optimization with Limited Memory COLT 2019
The Complexity of Making the Gradient Small in Stochastic Convex Optimization COLT 2019
Training Well-Generalizing Classifiers for Fairness Metrics and Other Data-Dependent Constraints ICML 2019
Learning Non-Discriminatory Predictors COLT 2017