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ORCIDMichael Kapralov
Mikhail Kapralov
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- affiliation: EPFL, Switzerland
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2020 – today
- 2024
[c61]Yu Chen, Michael Kapralov, Mikhail Makarov, Davide Mazzali:
On the Streaming Complexity of Expander Decomposition. ICALP 2024: 46:1-46:20- [c60]Ce Jin, Michael Kapralov, Sepideh Mahabadi, Ali Vakilian:
Streaming Algorithms for Connectivity Augmentation. ICALP 2024: 93:1-93:20 - [c59]Moses Charikar, Michael Kapralov, Erik Waingarten:
A Quasi-Monte Carlo Data Structure for Smooth Kernel Evaluations. SODA 2024: 5118-5144 - [i52]Moses Charikar, Michael Kapralov, Erik Waingarten:
A Quasi-Monte Carlo Data Structure for Smooth Kernel Evaluations. CoRR abs/2401.02562 (2024) - [i51]Michael Kapralov, Mikhail Makarov, Christian Sohler:
On the adversarial robustness of Locality-Sensitive Hashing in Hamming space. CoRR abs/2402.09707 (2024) - [i50]Ce Jin, Michael Kapralov, Sepideh Mahabadi, Ali Vakilian:
Streaming Algorithms for Connectivity Augmentation. CoRR abs/2402.10806 (2024) - [i49]Yu Chen, Michael Kapralov, Mikhail Makarov, Davide Mazzali:
On the Streaming Complexity of Expander Decomposition. CoRR abs/2404.16701 (2024) - 2023
- [j7]Maciej Besta
, Marc Fischer, Vasiliki Kalavri, Michael Kapralov, Torsten Hoefler:
Practice of Streaming Processing of Dynamic Graphs: Concepts, Models, and Systems. IEEE Trans. Parallel Distributed Syst. 34(6): 1860-1876 (2023) - [c58]Sepehr Assadi, Michael Kapralov, Huacheng Yu:
On Constructing Spanners from Random Gaussian Projections. APPROX/RANDOM 2023: 57:1-57:18 - [c57]Arnold Filtser, Michael Kapralov, Mikhail Makarov:
Expander Decomposition in Dynamic Streams. ITCS 2023: 50:1-50:13 - [c56]Michael Kapralov, Akash Kumar, Silvio Lattanzi, Aida Mousavifar:
Learning Hierarchical Cluster Structure of Graphs in Sublinear Time. SODA 2023: 925-939 - [c55]Michael Kapralov, Hannah Lawrence, Mikhail Makarov, Cameron Musco, Kshiteej Sheth:
Toeplitz Low-Rank Approximation with Sublinear Query Complexity. SODA 2023: 4127-4158 - [c54]Karl Bringmann, Michael Kapralov, Mikhail Makarov, Vasileios Nakos, Amir Yagudin, Amir Zandieh:
Traversing the FFT Computation Tree for Dimension-Independent Sparse Fourier Transforms. SODA 2023: 4768-4845 - 2022
- [c53]Michael Kapralov, Mikhail Makarov, Sandeep Silwal, Christian Sohler, Jakab Tardos:
Motif Cut Sparsifiers. FOCS 2022: 389-398 - [c52]Ashish Chiplunkar, John Kallaugher, Michael Kapralov, Eric Price:
Factorial Lower Bounds for (Almost) Random Order Streams. FOCS 2022: 486-497 - [c51]Michael Kapralov, Amulya Musipatla, Jakab Tardos, David P. Woodruff, Samson Zhou:
Noisy Boolean Hidden Matching with Applications. ITCS 2022: 91:1-91:19 - [c50]John Kallaugher, Michael Kapralov, Eric Price:
Simulating Random Walks in Random Streams. SODA 2022: 3091-3126 - [i48]Michael Kapralov, Mikhail Makarov, Sandeep Silwal, Christian Sohler, Jakab Tardos:
Motif Cut Sparsifiers. CoRR abs/2204.09951 (2022) - [i47]Michael Kapralov, Akash Kumar, Silvio Lattanzi, Aida Mousavifar:
Learning Hierarchical Structure of Clusterable Graphs. CoRR abs/2207.02581 (2022) - [i46]Sepehr Assadi, Michael Kapralov, Huacheng Yu:
On Constructing Spanners from Random Gaussian Projections. CoRR abs/2209.14775 (2022) - [i45]Michael Kapralov, Hannah Lawrence, Mikhail Makarov, Cameron Musco, Kshiteej Sheth:
Toeplitz Low-Rank Approximation with Sublinear Query Complexity. CoRR abs/2211.11328 (2022) - [i44]Arnold Filtser, Michael Kapralov, Mikhail Makarov:
Expander Decomposition in Dynamic Streams. CoRR abs/2211.11384 (2022) - 2021
- [c49]Michael Kapralov, Robert Krauthgamer, Jakab Tardos, Yuichi Yoshida:
Spectral Hypergraph Sparsifiers of Nearly Linear Size. FOCS 2021: 1159-1170 - [c48]Michael Kapralov, Silvio Lattanzi, Navid Nouri, Jakab Tardos:
Efficient and Local Parallel Random Walks. NeurIPS 2021: 21375-21387 - [c47]Grzegorz Gluch, Michael Kapralov, Silvio Lattanzi, Aida Mousavifar, Christian Sohler:
Spectral Clustering Oracles in Sublinear Time. SODA 2021: 1598-1617 - [c46]Michael Kapralov:
Space Lower Bounds for Approximating Maximum Matching in the Edge Arrival Model. SODA 2021: 1874-1893 - [c45]Arnold Filtser, Michael Kapralov, Navid Nouri:
Graph Spanners by Sketching in Dynamic Streams and the Simultaneous Communication Model. SODA 2021: 1894-1913 - [c44]Michael Kapralov, Gilbert Maystre, Jakab Tardos:
Communication Efficient Coresets for Maximum Matching. SOSA 2021: 156-164 - [c43]Michael Kapralov, Robert Krauthgamer, Jakab Tardos, Yuichi Yoshida:
Towards tight bounds for spectral sparsification of hypergraphs. STOC 2021: 598-611 - [i43]Grzegorz Gluch, Michael Kapralov, Silvio Lattanzi, Aida Mousavifar, Christian Sohler:
Spectral Clustering Oracles in Sublinear Time. CoRR abs/2101.05549 (2021) - [i42]Michael Kapralov:
Space Lower Bounds for Approximating Maximum Matching in the Edge Arrival Model. CoRR abs/2103.11669 (2021) - [i41]Michael Kapralov, Robert Krauthgamer, Jakab Tardos, Yuichi Yoshida:
Spectral Hypergraph Sparsifiers of Nearly Linear Size. CoRR abs/2106.02353 (2021) - [i40]Michael Kapralov, Amulya Musipatla, Jakab Tardos, David P. Woodruff, Samson Zhou:
Noisy Boolean Hidden Matching with Applications. CoRR abs/2107.02578 (2021) - [i39]Karl Bringmann, Michael Kapralov, Mikhail Makarov, Vasileios Nakos, Amir Yagudin, Amir Zandieh:
Sparse Fourier Transform by traversing Cooley-Tukey FFT computation graphs. CoRR abs/2107.07347 (2021) - [i38]Ashish Chiplunkar, John Kallaugher, Michael Kapralov, Eric Price:
Approximating Local Graph Structure in Almost Random Order Streams. CoRR abs/2110.10091 (2021) - [i37]Michael Kapralov, Silvio Lattanzi, Navid Nouri, Jakab Tardos:
Efficient and Local Parallel Random Walks. CoRR abs/2112.00655 (2021) - [i36]John Kallaugher, Michael Kapralov, Eric Price:
Simulating Random Walks in Random Streams. CoRR abs/2112.07532 (2021) - 2020
- [c42]Amir Zandieh, Navid Nouri, Ameya Velingker, Michael Kapralov, Ilya P. Razenshteyn:
Scaling up Kernel Ridge Regression via Locality Sensitive Hashing. AISTATS 2020: 4088-4097 - [c41]Moses Charikar, Michael Kapralov, Navid Nouri, Paris Siminelakis:
Kernel Density Estimation through Density Constrained Near Neighbor Search. FOCS 2020: 172-183 - [c40]Thomas D. Ahle, Michael Kapralov, Jakob Bæk Tejs Knudsen, Rasmus Pagh, Ameya Velingker, David P. Woodruff, Amir Zandieh:
Oblivious Sketching of High-Degree Polynomial Kernels. SODA 2020: 141-160 - [c39]Marek Eliás, Michael Kapralov, Janardhan Kulkarni, Yin Tat Lee:
Differentially Private Release of Synthetic Graphs. SODA 2020: 560-578 - [c38]Michael Kapralov, Slobodan Mitrovic, Ashkan Norouzi-Fard, Jakab Tardos:
Space Efficient Approximation to Maximum Matching Size from Uniform Edge Samples. SODA 2020: 1753-1772 - [c37]Michael Kapralov, Aida Mousavifar, Cameron Musco, Christopher Musco, Navid Nouri, Aaron Sidford, Jakab Tardos:
Fast and Space Efficient Spectral Sparsification in Dynamic Streams. SODA 2020: 1814-1833 - [i35]Michael Kapralov, Navid Nouri, Ilya P. Razenshteyn, Ameya Velingker, Amir Zandieh:
Scaling up Kernel Ridge Regression via Locality Sensitive Hashing. CoRR abs/2003.09756 (2020) - [i34]Arnold Filtser, Michael Kapralov, Navid Nouri:
Graph Spanners by Sketching in Dynamic Streams and the Simultaneous Communication Model. CoRR abs/2007.14204 (2020) - [i33]Michael Kapralov, Gilbert Maystre, Jakab Tardos:
Communication Efficient Coresets for Maximum Matching. CoRR abs/2011.06481 (2020) - [i32]Michael Kapralov, Robert Krauthgamer, Jakab Tardos, Yuichi Yoshida:
Towards Tight Bounds for Spectral Sparsification of Hypergraphs. CoRR abs/2011.06530 (2020) - [i31]Moses Charikar, Michael Kapralov, Navid Nouri, Paris Siminelakis:
Kernel Density Estimation through Density Constrained Near Neighbor Search. CoRR abs/2011.06997 (2020)
2010 – 2019
- 2019
- [j6]Ashish Goel, Michael Kapralov, Sanjeev Khanna:
Perfect Matchings in Õ (n 1.5) Time in Regular Bipartite Graphs. Comb. 39(2): 323-354 (2019) - [c36]Buddhima Gamlath, Michael Kapralov, Andreas Maggiori, Ola Svensson, David Wajc:
Online Matching with General Arrivals. FOCS 2019: 26-37 - [c35]Sepehr Assadi, Michael Kapralov, Sanjeev Khanna:
A Simple Sublinear-Time Algorithm for Counting Arbitrary Subgraphs via Edge Sampling. ITCS 2019: 6:1-6:20 - [c34]Andisheh Amrollahi, Amir Zandieh, Michael Kapralov, Andreas Krause:
Efficiently Learning Fourier Sparse Set Functions. NeurIPS 2019: 15094-15103 - [c33]Michael Kapralov, Ameya Velingker, Amir Zandieh:
Dimension-independent Sparse Fourier Transform. SODA 2019: 2709-2728 - [c32]Michael Kapralov, Dmitry Krachun:
An optimal space lower bound for approximating MAX-CUT. STOC 2019: 277-288 - [c31]Haim Avron, Michael Kapralov, Cameron Musco, Christopher Musco, Ameya Velingker, Amir Zandieh:
A universal sampling method for reconstructing signals with simple Fourier transforms. STOC 2019: 1051-1063 - [i30]Michael Kapralov, Ameya Velingker, Amir Zandieh:
Dimension-independent Sparse Fourier Transform. CoRR abs/1902.10633 (2019) - [i29]Michael Kapralov, Navid Nouri, Aaron Sidford, Jakab Tardos:
Dynamic Streaming Spectral Sparsification in Nearly Linear Time and Space. CoRR abs/1903.12150 (2019) - [i28]Michael Kapralov, Aida Mousavifar, Cameron Musco, Christopher Musco, Navid Nouri:
Faster Spectral Sparsification in Dynamic Streams. CoRR abs/1903.12165 (2019) - [i27]Buddhima Gamlath, Michael Kapralov, Andreas Maggiori, Ola Svensson, David Wajc:
Online Matching with General Arrivals. CoRR abs/1904.08255 (2019) - [i26]Michael Kapralov, Slobodan Mitrovic, Ashkan Norouzi-Fard, Jakab Tardos:
Space Efficient Approximation to Maximum Matching Size from Uniform Edge Samples. CoRR abs/1907.05725 (2019) - [i25]Michael Kapralov, Rasmus Pagh, Ameya Velingker, David P. Woodruff, Amir Zandieh:
Oblivious Sketching of High-Degree Polynomial Kernels. CoRR abs/1909.01410 (2019) - [i24]Maciej Besta, Marc Fischer, Vasiliki Kalavri, Michael Kapralov, Torsten Hoefler:
Practice of Streaming and Dynamic Graphs: Concepts, Models, Systems, and Parallelism. CoRR abs/1912.12740 (2019) - 2018
- [c30]Ashish Chiplunkar, Michael Kapralov, Sanjeev Khanna, Aida Mousavifar, Yuval Peres:
Testing Graph Clusterability: Algorithms and Lower Bounds. FOCS 2018: 497-508 - [c29]John Kallaugher, Michael Kapralov, Eric Price:
The Sketching Complexity of Graph and Hypergraph Counting. FOCS 2018: 556-567 - [i23]Haim Avron, Michael Kapralov, Cameron Musco, Christopher Musco, Ameya Velingker, Amir Zandieh:
Random Fourier Features for Kernel Ridge Regression: Approximation Bounds and Statistical Guarantees. CoRR abs/1804.09893 (2018) - [i22]Ashish Chiplunkar, Michael Kapralov, Sanjeev Khanna, Aida Mousavifar, Yuval Peres:
Testing Graph Clusterability: Algorithms and Lower Bounds. CoRR abs/1808.04807 (2018) - [i21]John Kallaugher, Michael Kapralov, Eric Price:
The Sketching Complexity of Graph and Hypergraph Counting. CoRR abs/1808.04995 (2018) - [i20]Sepehr Assadi, Michael Kapralov, Sanjeev Khanna:
A Simple Sublinear-Time Algorithm for Counting Arbitrary Subgraphs via Edge Sampling. CoRR abs/1811.07780 (2018) - [i19]Michael Kapralov, Dmitry Krachun:
An Optimal Space Lower Bound for Approximating MAX-CUT. CoRR abs/1811.10879 (2018) - [i18]Haim Avron, Michael Kapralov, Cameron Musco, Christopher Musco, Ameya Velingker, Amir Zandieh:
A Universal Sampling Method for Reconstructing Signals with Simple Fourier Transforms. CoRR abs/1812.08723 (2018) - 2017
- [j5]Michael Kapralov, Yin Tat Lee, Cameron Musco, Christopher Musco, Aaron Sidford:
Single Pass Spectral Sparsification in Dynamic Streams. SIAM J. Comput. 46(1): 456-477 (2017) - [c28]Michael Kapralov, Jelani Nelson, Jakub Pachocki, Zhengyu Wang, David P. Woodruff, Mobin Yahyazadeh:
Optimal Lower Bounds for Universal Relation, and for Samplers and Finding Duplicates in Streams. FOCS 2017: 475-486 - [c27]Michael Kapralov:
Sample Efficient Estimation and Recovery in Sparse FFT via Isolation on Average. FOCS 2017: 651-662 - [c26]Haim Avron, Michael Kapralov, Cameron Musco, Christopher Musco, Ameya Velingker, Amir Zandieh:
Random Fourier Features for Kernel Ridge Regression: Approximation Bounds and Statistical Guarantees. ICML 2017: 253-262 - [c25]Michael Kapralov, Sanjeev Khanna, Madhu Sudan, Ameya Velingker:
(1 + Ω(1))-Αpproximation to MAX-CUT Requires Linear Space. SODA 2017: 1703-1722 - [c24]Volkan Cevher, Michael Kapralov, Jonathan Scarlett, Amir Zandieh:
An adaptive sublinear-time block sparse fourier transform. STOC 2017: 702-715 - [i17]Volkan Cevher, Michael Kapralov, Jonathan Scarlett, Amir Zandieh:
An Adaptive Sublinear-Time Block Sparse Fourier Transform. CoRR abs/1702.01286 (2017) - [i16]Michael Kapralov, Jelani Nelson, Jakub Pachocki, Zhengyu Wang, David P. Woodruff, Mobin Yahyazadeh:
Optimal lower bounds for universal relation, and for samplers and finding duplicates in streams. CoRR abs/1704.00633 (2017) - [i15]Michael Kapralov:
Sample Efficient Estimation and Recovery in Sparse FFT via Isolation on Average. CoRR abs/1708.04544 (2017) - 2016
- [c23]Michael Kapralov, Vamsi K. Potluru, David P. Woodruff:
How to Fake Multiply by a Gaussian Matrix. ICML 2016: 2101-2110 - [c22]Venkatesan T. Chakaravarthy, Michael Kapralov, Prakash Murali, Fabrizio Petrini, Xinyu Que, Yogish Sabharwal, Baruch Schieber:
Subgraph Counting: Color Coding Beyond Trees. IPDPS 2016: 2-11 - [c21]Michael Kapralov:
Sparse fourier transform in any constant dimension with nearly-optimal sample complexity in sublinear time. STOC 2016: 264-277 - [i14]Venkatesan T. Chakaravarthy, Michael Kapralov, Prakash Murali, Fabrizio Petrini, Xinyu Que, Yogish Sabharwal, Baruch Schieber:
Subgraph Counting: Color Coding Beyond Trees. CoRR abs/1602.04478 (2016) - [i13]Michael Kapralov:
Sparse Fourier Transform in Any Constant Dimension with Nearly-Optimal Sample Complexity in Sublinear Time. CoRR abs/1604.00845 (2016) - [i12]Michael Kapralov, Vamsi K. Potluru, David P. Woodruff:
How to Fake Multiply by a Gaussian Matrix. CoRR abs/1606.05732 (2016) - 2015
- [c20]Michael Kapralov:
Smooth Tradeoffs between Insert and Query Complexity in Nearest Neighbor Search. PODS 2015: 329-342 - [c19]Michael Kapralov, Sanjeev Khanna, Madhu Sudan:
Streaming Lower Bounds for Approximating MAX-CUT. SODA 2015: 1263-1282 - 2014
- [c18]Piotr Indyk, Michael Kapralov:
Sample-Optimal Fourier Sampling in Any Constant Dimension. FOCS 2014: 514-523 - [c17]Michael Kapralov, Yin Tat Lee, Cameron Musco, Christopher Musco, Aaron Sidford:
Single Pass Spectral Sparsification in Dynamic Streams. FOCS 2014: 561-570 - [c16]Michael Kapralov, David P. Woodruff:
Spanners and sparsifiers in dynamic streams. PODC 2014: 272-281 - [c15]Piotr Indyk, Michael Kapralov, Eric Price:
(Nearly) Sample-Optimal Sparse Fourier Transform. SODA 2014: 480-499 - [c14]Michael Kapralov, Sanjeev Khanna, Madhu Sudan:
Approximating matching size from random streams. SODA 2014: 734-751 - [i11]Piotr Indyk, Michael Kapralov:
Sample-Optimal Fourier Sampling in Any Constant Dimension - Part I. CoRR abs/1403.5804 (2014) - [i10]Michael Kapralov, Yin Tat Lee, Cameron Musco, Christopher Musco, Aaron Sidford:
Single Pass Spectral Sparsification in Dynamic Streams. CoRR abs/1407.1289 (2014) - [i9]Michael Kapralov, Sanjeev Khanna, Madhu Sudan:
Streaming Lower Bounds for Approximating MAX-CUT. CoRR abs/1409.2138 (2014) - 2013
- [j4]Ashish Goel, Michael Kapralov, Sanjeev Khanna:
Perfect Matchings in O(nlog n) Time in Regular Bipartite Graphs. SIAM J. Comput. 42(3): 1392-1404 (2013) - [c13]Michael Kapralov, Ian Post, Jan Vondrák:
Online Submodular Welfare Maximization: Greedy is Optimal. SODA 2013: 1216-1225 - [c12]Michael Kapralov, Kunal Talwar:
On differentially private low rank approximation. SODA 2013: 1395-1414 - [c11]Michael Kapralov:
Better bounds for matchings in the streaming model. SODA 2013: 1679-1697 - 2012
- [c10]Debojyoti Dutta, Michael Kapralov, Ian Post, Rajendra Shinde:
Embedding Paths into Trees: VM Placement to Minimize Congestion. ESA 2012: 431-442 - [c9]Michael Kapralov, Rina Panigrahy:
NNS Lower Bounds via Metric Expansion for l ∞ and EMD. ICALP (1) 2012: 545-556 - [c8]Michael Kapralov, Rina Panigrahy:
Spectral sparsification via random spanners. ITCS 2012: 393-398 - [c7]Ashish Goel, Michael Kapralov, Sanjeev Khanna:
On the communication and streaming complexity of maximum bipartite matching. SODA 2012: 468-485 - [i8]Debojyoti Dutta, Michael Kapralov, Ian Post, Rajendra Shinde:
Optimal bandwidth-aware VM allocation for Infrastructure-as-a-Service. CoRR abs/1202.3683 (2012) - [i7]Ashish Goel, Michael Kapralov, Ian Post:
Single pass sparsification in the streaming model with edge deletions. CoRR abs/1203.4900 (2012) - [i6]Mikhail Kapralov, Ian Post, Jan Vondrák:
Online and stochastic variants of welfare maximization. CoRR abs/1204.1025 (2012) - [i5]Michael Kapralov:
Improved lower bounds for matchings in the streaming model. CoRR abs/1206.2269 (2012) - 2011
- [c6]Michael Kapralov, Rina Panigrahy:
Multiplicative Approximations of Random Walk Transition Probabilities. APPROX-RANDOM 2011: 266-276 - [c5]Michael Kapralov, Rina Panigrahy:
Prediction strategies without loss. NIPS 2011: 828-836 - 2010
- [j3]Ashish Goel, Michael Kapralov, Sanjeev Khanna:
Perfect matchings via uniform sampling in regular bipartite graphs. ACM Trans. Algorithms 6(2): 27:1-27:13 (2010) - [c4]Bahman Bahmani, Michael Kapralov:
Improved Bounds for Online Stochastic Matching. ESA (1) 2010: 170-181 - [c3]Ashish Goel, Michael Kapralov, Sanjeev Khanna:
Perfect matchings in o(n log n) time in regular bipartite graphs. STOC 2010: 39-46 - [i4]Ashish Goel, Michael Kapralov, Sanjeev Khanna:
Graph Sparsification via Refinement Sampling. CoRR abs/1004.4915 (2010) - [i3]Michael Kapralov, Rina Panigrahy:
Prediction strategies without loss. CoRR abs/1008.3672 (2010)
2000 – 2009
- 2009
- [c2]Ye Chen, Michael Kapralov, Dmitry Pavlov, John F. Canny:
Factor Modeling for Advertisement Targeting. NIPS 2009: 324-332 - [c1]Ashish Goel, Michael Kapralov, Sanjeev Khanna:
Perfect matchings via uniform sampling in regular bipartite graphs. SODA 2009: 11-17 - [i2]Ashish Goel, Michael Kapralov, Sanjeev Khanna:
Perfect Matchings in O(n \log n) Time in Regular Bipartite Graphs. CoRR abs/0909.3346 (2009) - 2008
- [j2]Mikhail Kapralov, Alexander Katsevich:
A Study of 1PI Algorithms for a General Class of Curves. SIAM J. Imaging Sci. 1(4): 418-459 (2008) - [i1]Ashish Goel, Michael Kapralov, Sanjeev Khanna:
Perfect Matchings via Uniform Sampling in Regular Bipartite Graphs. CoRR abs/0811.2457 (2008) - 2007
- [j1]Alexander Katsevich, Mikhail Kapralov:
Filtered Backprojection Inversion of the Cone Beam Transform for a General Class of Curves. SIAM J. Appl. Math. 68(2): 334-353 (2007)
Coauthor Index