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Sushant Sachdeva
Sushant Sachdeva
UToronto, Associate Professor. Vector Institute Affiliate
Verified email at cs.toronto.edu - Homepage
Title
Cited by
Cited by
Year
Maximum flow and minimum-cost flow in almost-linear time
L Chen, R Kyng, YP Liu, R Peng, MP Gutenberg, S Sachdeva
FOCS 2022. (IEEE 63rd Annual Symposium on Foundations of Computer Science …, 2022
317*2022
Approximate Gaussian Elimination for Laplacians-fast, sparse, and simple
R Kyng, S Sachdeva
FOCS 2016. (IEEE 57th Annual Symposium on Foundations of Computer Science …, 2016
2092016
Sparsified cholesky and multigrid solvers for connection laplacians
R Kyng, YT Lee, R Peng, S Sachdeva, DA Spielman
STOC 2016. (Proceedings of the forty-eighth annual ACM symposium on Theory …, 2016
1572016
Which algorithmic choices matter at which batch sizes? insights from a noisy quadratic model
G Zhang, L Li, Z Nado, J Martens, S Sachdeva, G Dahl, C Shallue, ...
(NeurIPS 2019) Advances in Neural Information Processing Systems, 8196-8207, 2019
1492019
Approximating the exponential, the lanczos method and an Õ(m)-time spectral algorithm for balanced separator
L Orecchia, S Sachdeva, NK Vishnoi
STOC 2012 (Proceedings of the 44th symposium on Theory of Computing), 1141-1160, 2012
1312012
Faster Algorithms via Approximation Theory
S Sachdeva, NK Vishnoi
Foundations and Trends® in Theoretical Computer Science 9 (2), 125-210, 2014
1182014
Provable ICA with unknown Gaussian noise, and implications for Gaussian mixtures and autoencoders
S Arora, R Ge, A Moitra, S Sachdeva
Algorithmica 72 (1), 215-236, 2015
1032015
Algorithms for Lipschitz learning on graphs
R Kyng, A Rao, S Sachdeva, DA Spielman
Proceedings of The 28th Conference on Learning Theory, 1190-1223, 2015
972015
Sampling random spanning trees faster than matrix multiplication
D Durfee, R Kyng, J Peebles, AB Rao, S Sachdeva
Proceedings of the 49th Annual ACM SIGACT Symposium on Theory of Computing …, 2017
872017
Graph sparsification, spectral sketches, and faster resistance computation via short cycle decompositions
T Chu, Y Gao, R Peng, S Sachdeva, S Sawlani, J Wang
SIAM Journal on Computing 52 (6), FOCS18-85-FOCS18-157, 2020
792020
Iterative Refinement for p-norm Regression
D Adil, R Kyng, R Peng, S Sachdeva
Proceedings of the Thirtieth Annual ACM-SIAM Symposium on Discrete …, 2019
782019
Finding overlapping communities in social networks: Toward a rigorous approach
S Arora, R Ge, S Sachdeva, G Schoenebeck
Proceedings of the 13th ACM Conference on Electronic Commerce, 37-54, 2012
672012
Fast, Provable Algorithms for Isotonic Regression in all L_p-norms
R Kyng, A Rao, S Sachdeva
Advances in Neural Information Processing Systems, 2701-2709, 2015
662015
Convergence Results for Neural Networks via Electrodynamics
R Panigrahy, A Rahimi, S Sachdeva, Q Zhang
9th Innovations in Theoretical Computer Science Conference (ITCS 2018) 94 …, 2017
57*2017
Regularized linear autoencoders recover the principal components, eventually
X Bao, J Lucas, S Sachdeva, RB Grosse
Advances in Neural Information Processing Systems 33, 2020
452020
Flows in almost linear time via adaptive preconditioning
R Kyng, R Peng, S Sachdeva, D Wang
Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing …, 2019
452019
Fast, provably convergent IRLS algorithm for p-norm linear regression
D Adil, R Peng, S Sachdeva
Advances in Neural Information Processing Systems, 14189-14200, 2019
432019
Optimal inapproximability for scheduling problems via structural hardness for hypergraph vertex cover
S Sachdeva, R Saket
Computational Complexity (CCC), 2013 IEEE Conference on, 219-229, 2013
392013
A deterministic almost-linear time algorithm for minimum-cost flow
J van den Brand, L Chen, R Kyng, YP Liu, R Peng, MP Gutenberg, ...
64th IEEE Annual Symposium on Foundations of Computer Science, FOCS, 2023
382023
A framework for analyzing resparsification algorithms
R Kyng, J Pachocki, R Peng, S Sachdeva
Proceedings of the Twenty-Eighth Annual ACM-SIAM Symposium on Discrete …, 2017
382017
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Articles 1–20