← Authors

Brian Bullins

20 papers · 2016–2025 · 7 conferences · across top CS/AI conferences

Achievements

🧭 Keyword Pioneer 🐝 Cross-Pollinator (8) 🌈 Renaissance Researcher (5) πŸ—ΊοΈ Taxonomy Completionist (28) 🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge 🌍 Conference Polyglot (7) πŸƒ Academic Marathon (9) πŸ—ƒοΈ Keyword Collector (66) πŸš€ Conference Pioneer πŸ’Ž Century Club (20) πŸ”₯ Unstoppable (10) ❓ The Questioner

Conferences

ICML (6) NIPS (4) COLT (3) ICLR (3) ALT (2) IJCAI (1) JMLR (1)

Top co-authors

Elad Hazan (5) Ohad Shamir (4) Nathan Srebro (4) Site Bai (4) Naman Agarwal (4) Karan Singh (3) Blake E Woodworth (3) Cyril Zhang (2) Blake Woodworth (2) Yi Zhang (2)

Keywords

convex optimization (6) distributed optimization (3) variance reduction (2) lower bound (2) logistic regression (2) non-convex optimization (2) stochastic optimization (2) communication complexity (1) online learning (1) stochastic gradient (1) convergence analysis (1) sample complexity (1) policy gradient (1) adaptive regularization (1) stochastic gradient descent (1) oracle complexity (1) gradient descent (1) empirical risk minimization (1) transfer learning (1) learning theory (1)

Papers

Model Immunization from a Condition Number Perspective ICML 2025
Faster Acceleration for Steepest Descent COLT 2025
Stacey: Promoting Stochastic Steepest Descent via Accelerated $\ell_p$-Smooth Nonconvex Optimization ICML 2025
Tight Lower Bounds under Asymmetric High-Order HΓΆlder Smoothness and Uniform Convexity ICLR 2025
Local Composite Saddle Point Optimization ICLR 2024
Competitive Gradient Optimization ICML 2023
Variance-Reduced Conservative Policy Iteration ALT 2023
The Min-Max Complexity of Distributed Stochastic Convex Optimization with Intermittent Communication (Extended Abstract) IJCAI 2022
Towards Optimal Communication Complexity in Distributed Non-Convex Optimization NIPS 2022
A Stochastic Newton Algorithm for Distributed Convex Optimization NIPS 2021
The Min-Max Complexity of Distributed Stochastic Convex Optimization with Intermittent Communication COLT 2021
Unifying Width-Reduced Methods for Quasi-Self-Concordant Optimization NIPS 2021
Is Local SGD Better than Minibatch SGD? ICML 2020
Highly smooth minimization of non-smooth problems COLT 2020
Online Control with Adversarial Disturbances ICML 2019
Efficient Full-Matrix Adaptive Regularization ICML 2019
Generalize Across Tasks: Efficient Algorithms for Linear Representation Learning ALT 2019
Not-So-Random Features ICLR 2018
Second-Order Stochastic Optimization for Machine Learning in Linear Time JMLR 2017
The Limits of Learning with Missing Data NIPS 2016