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 | 251* | 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 | 229 | 2013 |
Accelerated methods for nonconvex optimization Y Carmon, JC Duchi, O Hinder, A Sidford SIAM Journal on Optimization 28 (2), 1751-1772, 2018 | 226 | 2018 |
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 | 224 | 2013 |
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 | 214 | 2014 |
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 | 181 | 2015 |
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 | 156 | 2015 |
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 | 130 | 2015 |
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 | 121 | 2017 |
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 | 111* | 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 | 106* | 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 | 99 | 2015 |
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 | 92* | 2018 |
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 | 92 | 2015 |
Accelerating stochastic gradient descent for least squares regression P Jain, SM Kakade, R Kidambi, P Netrapalli, A Sidford Conference On Learning Theory, 545-604, 2018 | 91 | 2018 |
Near-optimal time and sample complexities for solving Markov decision processes with a generative model A Sidford, M Wang, X Wu, LF Yang, Y Ye Proceedings of the 32nd International Conference on Neural Information …, 2018 | 87* | 2018 |
“Convex Until Proven Guilty”: Dimension-Free Acceleration of Gradient Descent on Non-Convex Functions Y Carmon, JC Duchi, O Hinder, A Sidford International Conference on Machine Learning, 654-663, 2017 | 83 | 2017 |
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 | 82 | 2016 |
Variance reduced value iteration and faster algorithms for solving markov decision processes A Sidford, M Wang, X Wu, Y Ye Proceedings of the Twenty-Ninth Annual ACM-SIAM Symposium on Discrete …, 2018 | 73 | 2018 |
Lower bounds for finding stationary points i Y Carmon, JC Duchi, O Hinder, A Sidford arXiv preprint arXiv:1710.11606, 2017 | 70 | 2017 |