Brian Bullins
Brian Bullins
Research Assistant Professor, TTI-Chicago
Verified email at - Homepage
Cited by
Cited by
Finding approximate local minima faster than gradient descent
N Agarwal, Z Allen-Zhu, B Bullins, E Hazan, T Ma
Proceedings of the 49th Annual ACM SIGACT Symposium on Theory of Computing …, 2017
Second-order stochastic optimization for machine learning in linear time
N Agarwal, B Bullins, E Hazan
The Journal of Machine Learning Research 18 (1), 4148-4187, 2017
Online control with adversarial disturbances
N Agarwal, B Bullins, E Hazan, S Kakade, K Singh
International Conference on Machine Learning, 111-119, 2019
Is local SGD better than minibatch SGD?
B Woodworth, KK Patel, S Stich, Z Dai, B Bullins, B Mcmahan, O Shamir, ...
International Conference on Machine Learning, 10334-10343, 2020
Efficient full-matrix adaptive regularization
N Agarwal, B Bullins, X Chen, E Hazan, K Singh, C Zhang, Y Zhang
International Conference on Machine Learning, 102-110, 2019
Adaptive regularization with cubics on manifolds
N Agarwal, N Boumal, B Bullins, C Cartis
arXiv preprint arXiv:1806.00065, 2018
The min-max complexity of distributed stochastic convex optimization with intermittent communication
BE Woodworth, B Bullins, O Shamir, N Srebro
Conference on Learning Theory, 4386-4437, 2021
Not-So-Random Features
B Bullins, C Zhang, Y Zhang
International Conference on Learning Representations, 2018
Fast minimization of structured convex quartics
B Bullins
arXiv preprint arXiv:1812.10349, 2018
Generalize across tasks: Efficient algorithms for linear representation learning
B Bullins, E Hazan, A Kalai, R Livni
Algorithmic Learning Theory, 235-246, 2019
Highly smooth minimization of non-smooth problems
B Bullins
Conference on Learning Theory, 988-1030, 2020
Higher-order methods for convex-concave min-max optimization and monotone variational inequalities
B Bullins, KA Lai
arXiv preprint arXiv:2007.04528, 2020
Higher-order accelerated methods for faster non-smooth optimization
B Bullins, R Peng
arXiv preprint arXiv:1906.01621, 2019
Spectral properties of modularity matrices
M Bolla, B Bullins, S Chaturapruek, S Chen, K Friedl
Linear Algebra and Its Applications 473, 359-376, 2015
Almost-linear-time Weighted -norm Solvers in Slightly Dense Graphs via Sparsification
D Adil, B Bullins, R Kyng, S Sachdeva
arXiv preprint arXiv:2102.06977, 2021
The limits of learning with missing data
B Bullins, E Hazan, T Koren
Advances in Neural Information Processing Systems 29, 2016
Line Search-Free Methods for Higher-Order Smooth Monotone Variational Inequalities
D Adil, B Bullins, A Jambulapati, S Sachdeva
arXiv preprint arXiv:2205.06167, 2022
A Stochastic Newton Algorithm for Distributed Convex Optimization
B Bullins, K Patel, O Shamir, N Srebro, BE Woodworth
Advances in Neural Information Processing Systems 34, 26818-26830, 2021
Unifying Width-Reduced Methods for Quasi-Self-Concordant Optimization
D Adil, B Bullins, S Sachdeva
Advances in Neural Information Processing Systems 34, 19122-19133, 2021
Efficient Higher-Order Optimization for Machine Learning
BA Bullins
Princeton University, 2019
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