Dan Garber
Dan Garber
Verified email at technion.ac.il - Homepage
Title
Cited by
Cited by
Year
Faster rates for the frank-wolfe method over strongly-convex sets
D Garber, E Hazan
International Conference on Machine Learning, 541-549, 2015
1382015
A linearly convergent variant of the conditional gradient algorithm under strong convexity, with applications to online and stochastic optimization
D Garber, E Hazan
SIAM Journal on Optimization 26 (3), 1493-1528, 2016
116*2016
Faster eigenvector computation via shift-and-invert preconditioning
D Garber, E Hazan, C Jin, C Musco, P Netrapalli, A Sidford
International Conference on Machine Learning, 2626-2634, 2016
86*2016
Fast and simple PCA via convex optimization
D Garber, E Hazan
arXiv preprint arXiv:1509.05647, 2015
862015
Online principal components analysis
C Boutsidis, D Garber, Z Karnin, E Liberty
Proceedings of the twenty-sixth annual ACM-SIAM symposium on Discrete …, 2014
742014
Online learning of eigenvectors
D Garber, E Hazan, T Ma
International Conference on Machine Learning, 560-568, 2015
432015
Approximating semidefinite programs in sublinear time
D Garber, E Hazan
Computer Science Department, Technion, 2012
402012
Linear-memory and decomposition-invariant linearly convergent conditional gradient algorithm for structured polytopes
D Garber, O Meshi
arXiv preprint arXiv:1605.06492, 2016
352016
Playing non-linear games with linear oracles
D Garber, E Hazan
2013 IEEE 54th Annual Symposium on Foundations of Computer Science, 420-428, 2013
342013
Efficient globally convergent stochastic optimization for canonical correlation analysis
W Wang, J Wang, D Garber, N Srebro
arXiv preprint arXiv:1604.01870, 2016
292016
Faster Projection-free Convex Optimization over the Spectrahedron
D Garber
arxiv, 2016
282016
Communication-efficient algorithms for distributed stochastic principal component analysis
D Garber, O Shamir, N Srebro
International Conference on Machine Learning, 1203-1212, 2017
272017
Efficient coordinate-wise leading eigenvector computation
J Wang, W Wang, D Garber, N Srebro
Algorithmic Learning Theory, 806-820, 2018
182018
Improved complexities of conditional gradient-type methods with applications to robust matrix recovery problems
D Garber, A Kaplan, S Sabach
Mathematical Programming, 1-24, 2019
17*2019
Stochastic Canonical Correlation Analysis.
C Gao, D Garber, N Srebro, J Wang, W Wang
Journal of Machine Learning Research 20 (167), 1-46, 2019
172019
Sublinear time algorithms for approximate semidefinite programming
D Garber, E Hazan
Mathematical Programming 158 (1), 329-361, 2016
162016
Efficient online linear optimization with approximation algorithms
D Garber
Mathematics of Operations Research 46 (1), 204-220, 2021
112021
Improved regret bounds for projection-free bandit convex optimization
D Garber, B Kretzu
International Conference on Artificial Intelligence and Statistics, 2196-2206, 2020
82020
Logarithmic regret for online gradient descent beyond strong convexity
D Garber
The 22nd International Conference on Artificial Intelligence and Statistics …, 2019
8*2019
Revisiting Frank-Wolfe for Polytopes: Strict Complementarity and Sparsity
D Garber
arXiv preprint arXiv:2006.00558, 2020
72020
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