Brian Bullins
21 papers · 2016–2026 · 7 conferences · across top CS/AI conferences
Achievements
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π Conference Polyglot (7) π Interdisciplinary Bridge π§ Keyword Pioneer π£ Hot Topic Early Bird π Academic Marathon (9)
π
Interdisciplinary Bridge
π
Conference Polyglot
(7)
π
Academic Marathon
(9)
ποΈ
Keyword Collector
(66)
π
Conference Pioneer
π
Century Club
(20)
π₯
Unstoppable
(10)
β
The Questioner
Conferences
ICML (6)
NIPS (4)
ALT (3)
COLT (3)
ICLR (3)
IJCAI (1)
JMLR (1)
Top co-authors
Keywords
convex optimization
(7)
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
Convex optimization with $p$-norm oracles
ALT 2026
Faster Acceleration for Steepest Descent
COLT 2025
Model Immunization from a Condition Number Perspective
ICML 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
Variance-Reduced Conservative Policy Iteration
ALT 2023
Competitive Gradient Optimization
ICML 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
Unifying Width-Reduced Methods for Quasi-Self-Concordant Optimization
NIPS 2021
The Min-Max Complexity of Distributed Stochastic Convex Optimization with Intermittent Communication
COLT 2021
A Stochastic Newton Algorithm for Distributed Convex Optimization
NIPS 2021
Highly smooth minimization of non-smooth problems
COLT 2020
Is Local SGD Better than Minibatch SGD?
ICML 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