Michael Kapralov

1.6k total citations
34 papers, 462 citations indexed

About

Michael Kapralov is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Computer Networks and Communications. According to data from OpenAlex, Michael Kapralov has authored 34 papers receiving a total of 462 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Artificial Intelligence, 16 papers in Computational Theory and Mathematics and 11 papers in Computer Networks and Communications. Recurrent topics in Michael Kapralov's work include Complexity and Algorithms in Graphs (16 papers), Sparse and Compressive Sensing Techniques (9 papers) and Advanced Graph Theory Research (8 papers). Michael Kapralov is often cited by papers focused on Complexity and Algorithms in Graphs (16 papers), Sparse and Compressive Sensing Techniques (9 papers) and Advanced Graph Theory Research (8 papers). Michael Kapralov collaborates with scholars based in United States, Switzerland and Israel. Michael Kapralov's co-authors include Sanjeev Khanna, Kunal Talwar, Piotr Indyk, Ashish Goel, Rina Panigrahy‎, Eric Price, Madhu Sudan, David P. Woodruff, Cameron Musco and Christopher Musco and has published in prestigious journals such as SIAM Journal on Computing, SIAM Journal on Applied Mathematics and Inverse Problems.

In The Last Decade

Michael Kapralov

34 papers receiving 441 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Michael Kapralov United States	15	213	197	158	106	86	34	462
Aditya Bhaskara United States	9	156 0.7×	175 0.9×	107 0.7×	51 0.5×	39 0.5×	38	397
François Le Gall Japan	8	317 1.5×	296 1.5×	105 0.7×	55 0.5×	36 0.4×	35	573
Ioannis Koutis United States	14	159 0.7×	275 1.4×	113 0.7×	125 1.2×	61 0.7×	41	569
Jelani Nelson United States	14	540 2.5×	236 1.2×	266 1.7×	137 1.3×	237 2.8×	38	854
Daniel M. Kane United States	15	460 2.2×	271 1.4×	145 0.9×	101 1.0×	125 1.5×	89	841
Christopher Musco United States	11	222 1.0×	66 0.3×	60 0.4×	84 0.8×	81 0.9×	26	415
Aaron Sidford United States	12	231 1.1×	318 1.6×	129 0.8×	41 0.4×	111 1.3×	37	546
Luis Rademacher United States	7	193 0.9×	98 0.5×	45 0.3×	98 0.9×	180 2.1×	26	401
Desh Ranjan United States	10	182 0.9×	187 0.9×	186 1.2×	42 0.4×	15 0.2×	30	500
W. Fernandez de la Véga France	15	160 0.8×	414 2.1×	315 2.0×	53 0.5×	30 0.3×	39	897

Countries citing papers authored by Michael Kapralov

Since Specialization

Citations

This map shows the geographic impact of Michael Kapralov's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Michael Kapralov with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Kapralov more than expected).

Fields of papers citing papers by Michael Kapralov

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael Kapralov. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Michael Kapralov. The network helps show where Michael Kapralov may publish in the future.

Co-authorship network of co-authors of Michael Kapralov

This figure shows the co-authorship network connecting the top 25 collaborators of Michael Kapralov. A scholar is included among the top collaborators of Michael Kapralov based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Michael Kapralov. Michael Kapralov is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Kapralov, Michael, et al.. (2020). Oblivious Sketching of High-Degree Polynomial Kernels. IT University Of Copenhagen (IT University of Copenhagen). 2 indexed citations

Kapralov, Michael, et al.. (2019). Efficiently Learning Fourier Sparse Set Functions. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 32. 15094–15103. 4 indexed citations

Assadi, Sepehr, Michael Kapralov, & Sanjeev Khanna. (2018). A Simple Sublinear-Time Algorithm for Counting Arbitrary Subgraphs via\n Edge Sampling. arXiv (Cornell University). 6 indexed citations

Kapralov, Michael, et al.. (2018). Testing Graph Clusterability: Algorithms and Lower Bounds. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 497–508. 6 indexed citations

Avron, Haim, et al.. (2017). Random Fourier Features for Kernel Ridge Regression: Approximation Bounds and Statistical Guarantees. International Conference on Machine Learning. 253–262. 15 indexed citations

Kapralov, Michael, Sanjeev Khanna, Madhu Sudan, & Ameya Velingker. (2017). (1 + Ω(1))-Αpproximation to MAX-CUT Requires Linear Space. 6 indexed citations

Kapralov, Michael, et al.. (2017). Single Pass Spectral Sparsification in Dynamic Streams. SIAM Journal on Computing. 46(1). 456–477. 18 indexed citations

Kapralov, Michael. (2016). Sparse fourier transform in any constant dimension with nearly-optimal sample complexity in sublinear time. 264–277. 14 indexed citations

Kapralov, Michael. (2015). Smooth Tradeoffs between Insert and Query Complexity in Nearest Neighbor Search. 329–342. 7 indexed citations

10.

Kapralov, Michael & David P. Woodruff. (2014). Spanners and sparsifiers in dynamic streams. 272–281. 16 indexed citations

11.

Indyk, Piotr, Michael Kapralov, & Eric Price. (2013). (Nearly) Sample-Optimal Sparse Fourier Transform. 480–499. 29 indexed citations

12.

Kapralov, Michael. (2013). Better bounds for matchings in the streaming model. Symposium on Discrete Algorithms. 1679–1697. 33 indexed citations

13.

Kapralov, Michael & Kunal Talwar. (2013). On differentially private low rank approximation. Symposium on Discrete Algorithms. 1395–1414. 35 indexed citations

14.

Kapralov, Michael. (2012). Improved lower bounds for matchings in the streaming model. arXiv (Cornell University). 3 indexed citations

15.

Goel, Ashish, Michael Kapralov, & Sanjeev Khanna. (2012). On the communication and streaming complexity of maximum bipartite matching. 468–485. 32 indexed citations

16.

Kapralov, Michael & Rina Panigrahy‎. (2010). Prediction without loss in multi-armed bandit problems. arXiv (Cornell University). 1 indexed citations

17.

Kapralov, Michael & Rina Panigrahy‎. (2010). Prediction strategies without loss. arXiv (Cornell University). 24. 828–836. 5 indexed citations

18.

Chen, Ye, Michael Kapralov, John Canny, & Dmitry Pavlov. (2009). Factor Modeling for Advertisement Targeting. Neural Information Processing Systems. 22. 324–332. 24 indexed citations

19.

Goel, Ashish, Michael Kapralov, & Sanjeev Khanna. (2009). Perfect Matchings via Uniform Sampling in Regular Bipartite Graphs. 11–17. 2 indexed citations

20.

Katsevich, Alexander & Michael Kapralov. (2007). Filtered Backprojection Inversion of the Cone Beam Transform for a General Class of Curves. SIAM Journal on Applied Mathematics. 68(2). 334–353. 7 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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