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ORCIDSushant Sachdeva
Person information
- affiliation: University of Toronto, Canada
- affiliation (former): Yale University, New Haven, Connecticut, USA
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Journal Articles
- 2023
[j8]Li Chen, Rasmus Kyng, Yang P. Liu, Richard Peng, Maximilian Probst Gutenberg
, Sushant Sachdeva:
Almost-Linear-Time Algorithms for Maximum Flow and Minimum-Cost Flow. Commun. ACM 66(12): 85-92 (2023)- [j7]Timothy Chu, Yu Gao, Richard Peng, Sushant Sachdeva, Saurabh Sawlani, Junxing Wang:
Graph Sparsification, Spectral Sketches, and Faster Resistance Computation via Short Cycle Decompositions. SIAM J. Comput. 52(6): S18-85 (2023) - 2016
- [j6]Sushant Sachdeva, Nisheeth K. Vishnoi:
The mixing time of the Dikin walk in a polytope - A simple proof. Oper. Res. Lett. 44(5): 630-634 (2016) - 2015
- [j5]Sanjeev Arora, Rong Ge, Ankur Moitra, Sushant Sachdeva:
Provable ICA with Unknown Gaussian Noise, and Implications for Gaussian Mixtures and Autoencoders. Algorithmica 72(1): 215-236 (2015) - [j4]Venkatesan Guruswami, Sushant Sachdeva, Rishi Saket:
Inapproximability of Minimum Vertex Cover on k-Uniform k-Partite Hypergraphs. SIAM J. Discret. Math. 29(1): 36-58 (2015) - 2014
- [j3]Frédéric Cazals, Tom Dreyfus, Sushant Sachdeva, N. Shah:
Greedy Geometric Algorithms for Collection of Balls, with Applications to Geometric Approximation and Molecular Coarse-Graining. Comput. Graph. Forum 33(6): 1-17 (2014) - [j2]Sushant Sachdeva, Nisheeth K. Vishnoi:
Faster Algorithms via Approximation Theory. Found. Trends Theor. Comput. Sci. 9(2): 125-210 (2014) - 2011
- [j1]Sébastien Loriot, Sushant Sachdeva, Karine Bastard, Chantal Prévost, Frédéric Cazals:
On the Characterization and Selection of Diverse Conformational Ensembles with Applications to Flexible Docking. IEEE ACM Trans. Comput. Biol. Bioinform. 8(2): 487-498 (2011)
Conference and Workshop Papers
- 2024
- [c38]Rajarshi Bhattacharjee, Gregory Dexter, Cameron Musco, Archan Ray, Sushant Sachdeva, David P. Woodruff:
Universal Matrix Sparsifiers and Fast Deterministic Algorithms for Linear Algebra. ITCS 2024: 13:1-13:24 - [c37]Gramoz Goranci, Monika Henzinger, Harald Räcke, Sushant Sachdeva, A. R. Sricharan:
Electrical Flows for Polylogarithmic Competitive Oblivious Routing. ITCS 2024: 55:1-55:22 - [c36]Jan van den Brand, Li Chen, Rasmus Kyng, Yang P. Liu, Richard Peng, Maximilian Probst Gutenberg, Sushant Sachdeva, Aaron Sidford:
Incremental Approximate Maximum Flow on Undirected Graphs in Subpolynomial Update Time. SODA 2024: 2980-2998 - [c35]Sally Dong, Gramoz Goranci, Lawrence Li, Sushant Sachdeva, Guanghao Ye:
Fast Algorithms for Separable Linear Programs. SODA 2024: 3558-3604 - 2023
- [c34]Jan van den Brand, Li Chen, Richard Peng, Rasmus Kyng, Yang P. Liu, Maximilian Probst Gutenberg, Sushant Sachdeva, Aaron Sidford:
A Deterministic Almost-Linear Time Algorithm for Minimum-Cost Flow. FOCS 2023: 503-514 - [c33]Lawrence Li, Sushant Sachdeva:
A New Approach to Estimating Effective Resistances and Counting Spanning Trees in Expander Graphs. SODA 2023: 2728-2745 - [c32]Li Chen, Rasmus Kyng, Maximilian Probst Gutenberg, Sushant Sachdeva:
A Simple Framework for Finding Balanced Sparse Cuts via APSP. SOSA 2023: 42-55 - [c31]Sushant Sachdeva, Yibin Zhao:
A Simple and Efficient Parallel Laplacian Solver. SPAA 2023: 315-325 - 2022
- [c30]Li Chen, Rasmus Kyng, Yang P. Liu, Richard Peng, Maximilian Probst Gutenberg, Sushant Sachdeva:
Maximum Flow and Minimum-Cost Flow in Almost-Linear Time. FOCS 2022: 612-623 - [c29]Vijay Keswani, Oren Mangoubi, Sushant Sachdeva, Nisheeth K. Vishnoi:
A Convergent and Dimension-Independent Min-Max Optimization Algorithm. ICML 2022: 10939-10973 - [c28]Sally Dong, Yu Gao, Gramoz Goranci, Yin Tat Lee, Richard Peng, Sushant Sachdeva, Guanghao Ye:
Nested Dissection Meets IPMs: Planar Min-Cost Flow in Nearly-Linear Time. SODA 2022: 124-153 - 2021
- [c27]Deeksha Adil, Brian Bullins, Rasmus Kyng, Sushant Sachdeva:
Almost-Linear-Time Weighted 𝓁p-Norm Solvers in Slightly Dense Graphs via Sparsification. ICALP 2021: 9:1-9:15 - [c26]Deeksha Adil, Brian Bullins, Sushant Sachdeva:
Unifying Width-Reduced Methods for Quasi-Self-Concordant Optimization. NeurIPS 2021: 19122-19133 - 2020
- [c25]Matthew Fahrbach, Gramoz Goranci, Richard Peng, Sushant Sachdeva, Chi Wang:
Faster Graph Embeddings via Coarsening. ICML 2020: 2953-2963 - [c24]Xuchan Bao, James Lucas, Sushant Sachdeva, Roger B. Grosse:
Regularized linear autoencoders recover the principal components, eventually. NeurIPS 2020 - [c23]Deeksha Adil, Sushant Sachdeva:
Faster p-norm minimizing flows, via smoothed q-norm problems. SODA 2020: 892-910 - 2019
- [c22]Krishnamurthy Viswanathan, Sushant Sachdeva, Andrew Tomkins, Sujith Ravi:
Improved Semi-Supervised Learning with Multiple Graphs. AISTATS 2019: 3032-3041 - [c21]Guodong Zhang, Lala Li, Zachary Nado, James Martens, Sushant Sachdeva, George E. Dahl, Christopher J. Shallue, Roger B. Grosse:
Which Algorithmic Choices Matter at Which Batch Sizes? Insights From a Noisy Quadratic Model. NeurIPS 2019: 8194-8205 - [c20]Deeksha Adil, Richard Peng, Sushant Sachdeva:
Fast, Provably convergent IRLS Algorithm for p-norm Linear Regression. NeurIPS 2019: 14166-14177 - [c19]Deeksha Adil, Rasmus Kyng, Richard Peng, Sushant Sachdeva:
Iterative Refinement for ℓp-norm Regression. SODA 2019: 1405-1424 - [c18]Yang P. Liu, Sushant Sachdeva, Zejun Yu:
Short Cycles via Low-Diameter Decompositions. SODA 2019: 2602-2615 - [c17]Rasmus Kyng, Richard Peng, Sushant Sachdeva, Di Wang:
Flows in almost linear time via adaptive preconditioning. STOC 2019: 902-913 - 2018
- [c16]Timothy Chu, Yu Gao, Richard Peng, Sushant Sachdeva, Saurabh Sawlani, Junxing Wang:
Graph Sparsification, Spectral Sketches, and Faster Resistance Computation, via Short Cycle Decompositions. FOCS 2018: 361-372 - [c15]Rina Panigrahy, Ali Rahimi, Sushant Sachdeva, Qiuyi Zhang:
Convergence Results for Neural Networks via Electrodynamics. ITCS 2018: 22:1-22:19 - [c14]Amey Bhangale, Subhash Khot, Swastik Kopparty, Sushant Sachdeva, Devanathan Thiruvenkatachari:
Near-optimal approximation algorithm for simultaneous Max-Cut. SODA 2018: 1407-1425 - 2017
- [c13]Rasmus Kyng, Jakub Pachocki, Richard Peng, Sushant Sachdeva:
A Framework for Analyzing Resparsification Algorithms. SODA 2017: 2032-2043 - [c12]David Durfee, Rasmus Kyng, John Peebles, Anup B. Rao, Sushant Sachdeva:
Sampling random spanning trees faster than matrix multiplication. STOC 2017: 730-742 - 2016
- [c11]Rasmus Kyng, Sushant Sachdeva:
Approximate Gaussian Elimination for Laplacians - Fast, Sparse, and Simple. FOCS 2016: 573-582 - [c10]Rasmus Kyng, Yin Tat Lee, Richard Peng, Sushant Sachdeva, Daniel A. Spielman:
Sparsified Cholesky and multigrid solvers for connection laplacians. STOC 2016: 842-850 - 2015
- [c9]Rasmus Kyng, Anup Rao, Sushant Sachdeva, Daniel A. Spielman:
Algorithms for Lipschitz Learning on Graphs. COLT 2015: 1190-1223 - [c8]Amey Bhangale, Swastik Kopparty, Sushant Sachdeva:
Simultaneous Approximation of Constraint Satisfaction Problems. ICALP (1) 2015: 193-205 - [c7]Rasmus Kyng, Anup Rao, Sushant Sachdeva:
Fast, Provable Algorithms for Isotonic Regression in all L_p-norms. NIPS 2015: 2719-2727 - 2013
- [c6]Sushant Sachdeva, Rishi Saket:
Optimal Inapproximability for Scheduling Problems via Structural Hardness for Hypergraph Vertex Cover. CCC 2013: 219-229 - 2012
- [c5]Sanjeev Arora, Arnab Bhattacharyya, Rajsekar Manokaran, Sushant Sachdeva:
Testing Permanent Oracles - Revisited. APPROX-RANDOM 2012: 362-373 - [c4]Sanjeev Arora, Rong Ge, Ankur Moitra, Sushant Sachdeva:
"Provable ICA with Unknown Gaussian Noise, with Implications for Gaussian Mixtures and Autoencoders". NIPS 2012: 2384-2392 - [c3]Sanjeev Arora, Rong Ge, Sushant Sachdeva, Grant Schoenebeck:
Finding overlapping communities in social networks: toward a rigorous approach. EC 2012: 37-54 - [c2]Lorenzo Orecchia, Sushant Sachdeva, Nisheeth K. Vishnoi:
Approximating the exponential, the lanczos method and an Õ(m)-time spectral algorithm for balanced separator. STOC 2012: 1141-1160 - 2011
- [c1]Sushant Sachdeva, Rishi Saket:
Nearly Optimal NP-Hardness of Vertex Cover on k-Uniform k-Partite Hypergraphs. APPROX-RANDOM 2011: 327-338
Informal and Other Publications
- 2023
- [i48]Gramoz Goranci, Monika Henzinger, Harald Räcke, Sushant Sachdeva, A. R. Sricharan:
Electrical Flows for Polylogarithmic Competitive Oblivious Routing. CoRR abs/2303.02491 (2023) - [i47]Sushant Sachdeva, Yibin Zhao:
A Simple and Efficient Parallel Laplacian Solver. CoRR abs/2304.14345 (2023) - [i46]Rajarshi Bhattacharjee, Gregory Dexter, Cameron Musco, Archan Ray, Sushant Sachdeva, David P. Woodruff:
Universal Matrix Sparsifiers and Fast Deterministic Algorithms for Linear Algebra. CoRR abs/2305.05826 (2023) - [i45]Jan van den Brand, Li Chen, Rasmus Kyng, Yang P. Liu, Richard Peng, Maximilian Probst Gutenberg, Sushant Sachdeva, Aaron Sidford:
A Deterministic Almost-Linear Time Algorithm for Minimum-Cost Flow. CoRR abs/2309.16629 (2023) - [i44]Sally Dong, Gramoz Goranci, Lawrence Li, Sushant Sachdeva, Guanghao Ye:
Fast Algorithms for Separable Linear Programs. CoRR abs/2310.16351 (2023) - [i43]Jan van den Brand, Li Chen, Rasmus Kyng, Yang P. Liu, Richard Peng, Maximilian Probst Gutenberg, Sushant Sachdeva, Aaron Sidford:
Incremental Approximate Maximum Flow on Undirected Graphs in Subpolynomial Update Time. CoRR abs/2311.03174 (2023) - [i42]Sushant Sachdeva, Anvith Thudi, Yibin Zhao:
Better Sparsifiers for Directed Eulerian Graphs. CoRR abs/2311.06232 (2023) - 2022
- [i41]Li Chen, Rasmus Kyng, Yang P. Liu, Richard Peng, Maximilian Probst Gutenberg, Sushant Sachdeva:
Maximum Flow and Minimum-Cost Flow in Almost-Linear Time. CoRR abs/2203.00671 (2022) - [i40]Sally Dong, Yu Gao, Gramoz Goranci, Yin Tat Lee, Richard Peng, Sushant Sachdeva, Guanghao Ye:
Nested Dissection Meets IPMs: Planar Min-Cost Flow in Nearly-Linear Time. CoRR abs/2205.01562 (2022) - [i39]Deeksha Adil, Brian Bullins, Arun Jambulapati, Sushant Sachdeva:
Optimal Methods for Higher-Order Smooth Monotone Variational Inequalities. CoRR abs/2205.06167 (2022) - [i38]Li Chen, Rasmus Kyng, Maximilian Probst Gutenberg, Sushant Sachdeva:
A Simple Framework for Finding Balanced Sparse Cuts via APSP. CoRR abs/2209.08845 (2022) - [i37]Lawrence Li, Sushant Sachdeva:
A New Approach to Estimating Effective Resistances and Counting Spanning Trees in Expander Graphs. CoRR abs/2211.01468 (2022) - [i36]Deeksha Adil, Rasmus Kyng, Richard Peng, Sushant Sachdeva:
Fast Algorithms for 𝓁p-Regression. CoRR abs/2211.03963 (2022) - 2021
- [i35]Deeksha Adil, Brian Bullins, Rasmus Kyng, Sushant Sachdeva:
Almost-linear-time Weighted 𝓁p-norm Solvers in Slightly Dense Graphs via Sparsification. CoRR abs/2102.06977 (2021) - [i34]Deeksha Adil, Brian Bullins, Sushant Sachdeva:
Unifying Width-Reduced Methods for Quasi-Self-Concordant Optimization. CoRR abs/2107.02432 (2021) - 2020
- [i33]Oren Mangoubi, Sushant Sachdeva, Nisheeth K. Vishnoi:
A Provably Convergent and Practical Algorithm for Min-max Optimization with Applications to GANs. CoRR abs/2006.12376 (2020) - [i32]Matthew Fahrbach, Gramoz Goranci, Richard Peng, Sushant Sachdeva, Chi Wang:
Faster Graph Embeddings via Coarsening. CoRR abs/2007.02817 (2020) - [i31]Xuchan Bao, James Lucas, Sushant Sachdeva, Roger B. Grosse:
Regularized linear autoencoders recover the principal components, eventually. CoRR abs/2007.06731 (2020) - 2019
- [i30]Deeksha Adil, Rasmus Kyng, Richard Peng, Sushant Sachdeva:
Iterative Refinement for 𝓁p-norm Regression. CoRR abs/1901.06764 (2019) - [i29]Rasmus Kyng, Richard Peng, Sushant Sachdeva, Di Wang:
Flows in Almost Linear Time via Adaptive Preconditioning. CoRR abs/1906.10340 (2019) - [i28]Guodong Zhang, Lala Li, Zachary Nado, James Martens, Sushant Sachdeva, George E. Dahl, Christopher J. Shallue, Roger B. Grosse:
Which Algorithmic Choices Matter at Which Batch Sizes? Insights From a Noisy Quadratic Model. CoRR abs/1907.04164 (2019) - [i27]Deeksha Adil, Richard Peng, Sushant Sachdeva:
Fast, Provably convergent IRLS Algorithm for p-norm Linear Regression. CoRR abs/1907.07167 (2019) - [i26]Deeksha Adil, Sushant Sachdeva:
Faster p-norm minimizing flows, via smoothed q-norm problems. CoRR abs/1910.10571 (2019) - 2018
- [i25]Amey Bhangale, Subhash Khot, Swastik Kopparty, Sushant Sachdeva, Devanathan Thiruvenkatachari:
Near-optimal approximation algorithm for simultaneous Max-Cut. CoRR abs/1801.04497 (2018) - [i24]Timothy Chu, Yu Gao, Richard Peng, Sushant Sachdeva, Saurabh Sawlani, Junxing Wang:
Graph Sparsification, Spectral Sketches, and Faster Resistance Computation, via Short Cycle Decompositions. CoRR abs/1805.12051 (2018) - [i23]Yang P. Liu, Sushant Sachdeva, Zejun Yu:
Short Cycles via Low-Diameter Decompositions. CoRR abs/1810.05143 (2018) - 2017
- [i22]Qiuyi Zhang, Rina Panigrahy, Sushant Sachdeva:
Electron-Proton Dynamics in Deep Learning. CoRR abs/1702.00458 (2017) - 2016
- [i21]Rasmus Kyng, Sushant Sachdeva:
Approximate Gaussian Elimination for Laplacians: Fast, Sparse, and Simple. CoRR abs/1605.02353 (2016) - [i20]Rasmus Kyng, Jakub Pachocki, Richard Peng, Sushant Sachdeva:
A Framework for Analyzing Resparsification Algorithms. CoRR abs/1611.06940 (2016) - [i19]David Durfee, Rasmus Kyng, John Peebles, Anup B. Rao, Sushant Sachdeva:
Sampling Random Spanning Trees Faster than Matrix Multiplication. CoRR abs/1611.07451 (2016) - 2015
- [i18]Rasmus Kyng, Anup Rao, Sushant Sachdeva, Daniel A. Spielman:
Algorithms for Lipschitz Learning on Graphs. CoRR abs/1505.00290 (2015) - [i17]Rasmus Kyng, Anup Rao, Sushant Sachdeva:
Fast, Provable Algorithms for Isotonic Regression in all ℓp-norms. CoRR abs/1507.00710 (2015) - [i16]Sushant Sachdeva, Nisheeth K. Vishnoi:
A Simple Analysis of the Dikin Walk. CoRR abs/1508.01977 (2015) - [i15]Rasmus Kyng, Yin Tat Lee, Richard Peng, Sushant Sachdeva, Daniel A. Spielman:
Sparsified Cholesky and Multigrid Solvers for Connection Laplacians. CoRR abs/1512.01892 (2015) - 2014
- [i14]Amey Bhangale, Swastik Kopparty, Sushant Sachdeva:
Simultaneous Approximation of Constraint Satisfaction Problems. CoRR abs/1407.7759 (2014) - [i13]Amey Bhangale, Swastik Kopparty, Sushant Sachdeva:
Simultaneous Approximation of Constraint Satisfaction Problems. Electron. Colloquium Comput. Complex. TR14 (2014) - 2013
- [i12]Pooya Hatami, Sushant Sachdeva, Madhur Tulsiani:
An Arithmetic Analogue of Fox's Triangle Removal Argument. CoRR abs/1304.4921 (2013) - [i11]Sushant Sachdeva, Nisheeth K. Vishnoi:
Matrix Inversion Is As Easy As Exponentiation. CoRR abs/1305.0526 (2013) - [i10]Sushant Sachdeva, Nisheeth K. Vishnoi:
Approximation Theory and the Design of Fast Algorithms. CoRR abs/1309.4882 (2013) - [i9]Venkatesan Guruswami, Sushant Sachdeva, Rishi Saket:
Inapproximability of Minimum Vertex Cover on k-uniform k-partite Hypergraphs. Electron. Colloquium Comput. Complex. TR13 (2013) - 2012
- [i8]Sanjeev Arora, Rong Ge, Ankur Moitra, Sushant Sachdeva:
Provable ICA with Unknown Gaussian Noise, and Implications for Gaussian Mixtures and Autoencoders. CoRR abs/1206.5349 (2012) - [i7]Sanjeev Arora, Arnab Bhattacharyya, Rajsekar Manokaran, Sushant Sachdeva:
Testing Permanent Oracles -- Revisited. CoRR abs/1207.4783 (2012) - [i6]Sanjeev Arora, Arnab Bhattacharyya, Rajsekar Manokaran, Sushant Sachdeva:
Testing Permanent Oracles - Revisited. Electron. Colloquium Comput. Complex. TR12 (2012) - 2011
- [i5]Sanjeev Arora, James R. Lee, Sushant Sachdeva:
A Reformulation of the Arora-Rao-Vazirani Structure Theorem. CoRR abs/1102.1456 (2011) - [i4]Sushant Sachdeva, Madhur Tulsiani:
Cuts in Cartesian Products of Graphs. CoRR abs/1105.3383 (2011) - [i3]Sushant Sachdeva, Rishi Saket:
Nearly Optimal NP-Hardness of Vertex Cover on k-Uniform k-Partite Hypergraphs. CoRR abs/1105.4175 (2011) - [i2]Lorenzo Orecchia, Sushant Sachdeva, Nisheeth K. Vishnoi:
Approximating the Exponential, the Lanczos Method and an \tilde{O}(m)-Time Spectral Algorithm for Balanced Separator. CoRR abs/1111.1491 (2011) - [i1]Sanjeev Arora, Rong Ge, Sushant Sachdeva, Grant Schoenebeck:
Finding Overlapping Communities in Social Networks: Toward a Rigorous Approach. CoRR abs/1112.1831 (2011)
Coauthor Index
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