Dan Garber
Dan Garber
Verifierad e-postadress på technion.ac.il - Startsida
Titel
Citeras av
Citeras av
År
Faster rates for the frank-wolfe method over strongly-convex sets
D Garber, E Hazan
International Conference on Machine Learning, 541-549, 2015
1542015
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
128*2016
Fast and simple PCA via convex optimization
D Garber, E Hazan
arXiv preprint arXiv:1509.05647, 2015
912015
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
89*2016
Online principal components analysis
C Boutsidis, D Garber, Z Karnin, E Liberty
Proceedings of the twenty-sixth annual ACM-SIAM symposium on Discrete …, 2014
772014
Online learning of eigenvectors
D Garber, E Hazan, T Ma
International Conference on Machine Learning, 560-568, 2015
452015
Linear-memory and decomposition-invariant linearly convergent conditional gradient algorithm for structured polytopes
D Garber, O Meshi
Advances in neural information processing systems 29, 1001-1009, 2016
412016
Playing non-linear games with linear oracles
D Garber, E Hazan
2013 IEEE 54th Annual Symposium on Foundations of Computer Science, 420-428, 2013
392013
Approximating semidefinite programs in sublinear time
D Garber, E Hazan
Computer Science Department, Technion, 2012
392012
Efficient globally convergent stochastic optimization for canonical correlation analysis
W Wang, J Wang, D Garber, N Srebro
arXiv preprint arXiv:1604.01870, 2016
322016
Faster Projection-free Convex Optimization over the Spectrahedron
D Garber
arxiv, 2016
302016
Communication-efficient algorithms for distributed stochastic principal component analysis
D Garber, O Shamir, N Srebro
International Conference on Machine Learning, 1203-1212, 2017
272017
Improved complexities of conditional gradient-type methods with applications to robust matrix recovery problems
D Garber, A Kaplan, S Sabach
Mathematical Programming 186 (1), 185-208, 2021
19*2021
Stochastic Canonical Correlation Analysis.
C Gao, D Garber, N Srebro, J Wang, W Wang
J. Mach. Learn. Res. 20, 167:1-167:46, 2019
182019
Efficient coordinate-wise leading eigenvector computation
J Wang, W Wang, D Garber, N Srebro
Algorithmic Learning Theory, 806-820, 2018
182018
Efficient online linear optimization with approximation algorithms
D Garber
arXiv preprint arXiv:1709.03093, 2017
16*2017
Sublinear time algorithms for approximate semidefinite programming
D Garber, E Hazan
Mathematical Programming 158 (1), 329-361, 2016
162016
Revisiting Frank-Wolfe for Polytopes: Strict Complementarity and Sparsity
D Garber
arXiv preprint arXiv:2006.00558, 2020
112020
Improved regret bounds for projection-free bandit convex optimization
D Garber, B Kretzu
International Conference on Artificial Intelligence and Statistics, 2196-2206, 2020
92020
Logarithmic regret for online gradient descent beyond strong convexity
D Garber
The 22nd International Conference on Artificial Intelligence and Statistics …, 2019
9*2019
Systemet kan inte utföra åtgärden just nu. Försök igen senare.
Artiklar 1–20