Sushant Sachdeva
Sushant Sachdeva
UToronto
Bestätigte E-Mail-Adresse bei cs.toronto.edu - Startseite
Titel
Zitiert von
Zitiert von
Jahr
Approximate Gaussian Elimination for Laplacians-fast, sparse, and simple
R Kyng, S Sachdeva
2016 IEEE 57th Annual Symposium on Foundations of Computer Science (FOCS …, 2016
1262016
Approximating the exponential, the lanczos method and an Õ(m)-time spectral algorithm for balanced separator
L Orecchia, S Sachdeva, NK Vishnoi
Proceedings of the 44th symposium on Theory of Computing, 1141-1160, 2012
1042012
Sparsified cholesky and multigrid solvers for connection laplacians
R Kyng, YT Lee, R Peng, S Sachdeva, DA Spielman
Proceedings of the forty-eighth annual ACM symposium on Theory of Computing …, 2016
942016
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
872015
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
622015
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
582012
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
542017
Faster Algorithms via Approximation Theory
S Sachdeva, NK Vishnoi
Foundations and Trends® in Theoretical Computer Science 9 (2), 125-210, 2014
532014
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
47*2017
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
442015
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, FOCS18-85-FOCS18-157, 2020
332020
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, ...
Advances in Neural Information Processing Systems, 8196-8207, 2019
312019
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
302019
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
292017
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
242013
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
142019
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
112019
Greedy Geometric Algorithms for Collection of Balls, with Applications to Geometric Approximation and Molecular Coarse‐Graining
F Cazals, T Dreyfus, S Sachdeva, N Shah
Computer Graphics Forum 33 (6), 1-17, 2014
11*2014
Nearly optimal NP-hardness of vertex cover on k-uniform k-partite hypergraphs
S Sachdeva, R Saket
Approximation, Randomization, and Combinatorial Optimization. Algorithms and …, 2011
112011
Inapproximability of minimum vertex cover on k-uniform k-partite hypergraphs
V Guruswami, S Sachdeva, R Saket
SIAM Journal on Discrete Mathematics 29 (1), 36-58, 2015
102015
Das System kann den Vorgang jetzt nicht ausführen. Versuchen Sie es später erneut.
Artikel 1–20