Aaron Sidford
TitleCited byYear
A simple, combinatorial algorithm for solving SDD systems in nearly-linear time
JA Kelner, L Orecchia, A Sidford, ZA Zhu
Proceedings of the forty-fifth annual ACM symposium on Theory of computing …, 2013
1822013
Path finding methods for linear programming: Solving linear programs in O (vrank) iterations and faster algorithms for maximum flow
YT Lee, A Sidford
2014 IEEE 55th Annual Symposium on Foundations of Computer Science, 424-433, 2014
170*2014
Efficient accelerated coordinate descent methods and faster algorithms for solving linear systems
YT Lee, A Sidford
2013 IEEE 54th Annual Symposium on Foundations of Computer Science, 147-156, 2013
1702013
An almost-linear-time algorithm for approximate max flow in undirected graphs, and its multicommodity generalizations
JA Kelner, YT Lee, L Orecchia, A Sidford
Proceedings of the twenty-fifth annual ACM-SIAM symposium on Discrete …, 2014
1622014
Accelerated methods for nonconvex optimization
Y Carmon, JC Duchi, O Hinder, A Sidford
SIAM Journal on Optimization 28 (2), 1751-1772, 2018
1462018
A faster cutting plane method and its implications for combinatorial and convex optimization
YT Lee, A Sidford, SC Wong
2015 IEEE 56th Annual Symposium on Foundations of Computer Science, 1049-1065, 2015
1302015
Uniform sampling for matrix approximation
MB Cohen, YT Lee, C Musco, C Musco, R Peng, A Sidford
Proceedings of the 2015 Conference on Innovations in Theoretical Computer …, 2015
1072015
Un-regularizing: approximate proximal point and faster stochastic algorithms for empirical risk minimization
R Frostig, R Ge, S Kakade, A Sidford
International Conference on Machine Learning, 2540-2548, 2015
1042015
Single pass spectral sparsification in dynamic streams
M Kapralov, YT Lee, CN Musco, CP Musco, A Sidford
SIAM Journal on Computing 46 (1), 456-477, 2017
892017
Streaming PCA: Matching matrix Bernstein and near-optimal finite sample guarantees for Oja’s algorithm
P Jain, C Jin, SM Kakade, P Netrapalli, A Sidford
Conference on learning theory, 1147-1164, 2016
82*2016
Robust shift-and-invert preconditioning: Faster and more sample efficient algorithms for eigenvector computation
D Garber, E Hazan, C Jin, SM Kakade, C Musco, P Netrapalli, A Sidford
ICML, 2016
81*2016
Competing with the empirical risk minimizer in a single pass
R Frostig, R Ge, SM Kakade, A Sidford
Conference on learning theory, 728-763, 2015
672015
Geometric median in nearly linear time
MB Cohen, YT Lee, G Miller, J Pachocki, A Sidford
Proceedings of the forty-eighth annual ACM symposium on Theory of Computing …, 2016
572016
Parallelizing stochastic gradient descent for least squares regression: mini-batching, averaging, and model misspecification
P Jain, S Kakade, R Kidambi, P Netrapalli, A Sidford
Journal of Machine Learning Research 18, 2018
53*2018
Convex until proven guilty: Dimension-free acceleration of gradient descent on non-convex functions
Y Carmon, JC Duchi, O Hinder, A Sidford
Proceedings of the 34th International Conference on Machine Learning-Volume …, 2017
512017
Lower bounds for finding stationary points i
Y Carmon, JC Duchi, O Hinder, A Sidford
Mathematical Programming, 1-50, 2017
492017
Efficient inverse maintenance and faster algorithms for linear programming
YT Lee, A Sidford
2015 IEEE 56th Annual Symposium on Foundations of Computer Science, 230-249, 2015
492015
Accelerating stochastic gradient descent for least squares regression
P Jain, SM Kakade, R Kidambi, P Netrapalli, A Sidford
arXiv preprint arXiv:1704.08227, 2017
47*2017
Almost-linear-time algorithms for markov chains and new spectral primitives for directed graphs
MB Cohen, J Kelner, J Peebles, R Peng, AB Rao, A Sidford, A Vladu
Proceedings of the 49th Annual ACM SIGACT Symposium on Theory of Computing …, 2017
412017
Efficient algorithms for large-scale generalized eigenvector computation and canonical correlation analysis
R Ge, C Jin, P Netrapalli, A Sidford
International Conference on Machine Learning, 2741-2750, 2016
362016
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Articles 1–20