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Bullins, Brian
21 publications
NeurIPS
2025
Balancing Gradient and Hessian Queries in Non-Convex Optimization
Deeksha Adil
,
Brian Bullins
,
Aaron Sidford
,
Chenyi Zhang
COLT
2025
Faster Acceleration for Steepest Descent
Cedar Site Bai
,
Brian Bullins
ICML
2025
Model Immunization from a Condition Number Perspective
Amber Yijia Zheng
,
Site Bai
,
Brian Bullins
,
Raymond A. Yeh
ICML
2025
Stacey: Promoting Stochastic Steepest Descent via Accelerated $\ell_p$-Smooth Nonconvex Optimization
Xinyu Luo
,
Site Bai
,
Bolian Li
,
Petros Drineas
,
Ruqi Zhang
,
Brian Bullins
ICLR
2025
Tight Lower Bounds Under Asymmetric High-Order Hölder Smoothness and Uniform Convexity
Site Bai
,
Brian Bullins
ICLR
2024
Local Composite Saddle Point Optimization
Site Bai
,
Brian Bullins
ICML
2023
Competitive Gradient Optimization
Abhijeet Vyas
,
Brian Bullins
,
Kamyar Azizzadenesheli
ALT
2023
Variance-Reduced Conservative Policy Iteration
Naman Agarwal
,
Brian Bullins
,
Karan Singh
IJCAI
2022
The Min-Max Complexity of Distributed Stochastic Convex Optimization with Intermittent Communication (Extended Abstract)
Blake E. Woodworth
,
Brian Bullins
,
Ohad Shamir
,
Nathan Srebro
NeurIPS
2022
Towards Optimal Communication Complexity in Distributed Non-Convex Optimization
Kumar Kshitij Patel
,
Lingxiao Wang
,
Blake E Woodworth
,
Brian Bullins
,
Nati Srebro
NeurIPS
2021
A Stochastic Newton Algorithm for Distributed Convex Optimization
Brian Bullins
,
Kshitij Patel
,
Ohad Shamir
,
Nathan Srebro
,
Blake E Woodworth
COLT
2021
The Min-Max Complexity of Distributed Stochastic Convex Optimization with Intermittent Communication
Blake E Woodworth
,
Brian Bullins
,
Ohad Shamir
,
Nathan Srebro
NeurIPS
2021
Unifying Width-Reduced Methods for Quasi-Self-Concordant Optimization
Deeksha Adil
,
Brian Bullins
,
Sushant Sachdeva
COLT
2020
Highly Smooth Minimization of Non-Smooth Problems
Brian Bullins
ICML
2020
Is Local SGD Better than Minibatch SGD?
Blake Woodworth
,
Kumar Kshitij Patel
,
Sebastian Stich
,
Zhen Dai
,
Brian Bullins
,
Brendan Mcmahan
,
Ohad Shamir
,
Nathan Srebro
ICML
2019
Efficient Full-Matrix Adaptive Regularization
Naman Agarwal
,
Brian Bullins
,
Xinyi Chen
,
Elad Hazan
,
Karan Singh
,
Cyril Zhang
,
Yi Zhang
ALT
2019
Generalize Across Tasks: Efficient Algorithms for Linear Representation Learning
Brian Bullins
,
Elad Hazan
,
Adam Kalai
,
Roi Livni
ICML
2019
Online Control with Adversarial Disturbances
Naman Agarwal
,
Brian Bullins
,
Elad Hazan
,
Sham Kakade
,
Karan Singh
ICLR
2018
Not-so-Random Features
Brian Bullins
,
Cyril Zhang
,
Yi Zhang
JMLR
2017
Second-Order Stochastic Optimization for Machine Learning in Linear Time
Naman Agarwal
,
Brian Bullins
,
Elad Hazan
NeurIPS
2016
The Limits of Learning with Missing Data
Brian Bullins
,
Elad Hazan
,
Tomer Koren