Minor Sparsifiers and the Distributed Laplacian Paradigm-Reference-Cited by-同舟云学术

Minor Sparsifiers and the Distributed Laplacian Paradigm

Published:2022-02 Issue: Volume: Page:
ISSN:
Container-title:2021 IEEE 62nd Annual Symposium on Foundations of Computer Science (FOCS)
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Author:

Forster Sebastian¹,Goranci Gramoz²,Liu Yang P.³,Peng Richard⁴,Sun Xiaorui⁵,Ye Mingquan⁵

Affiliation:

1. University of Salzburg,Department of Computer Sciences,Salzburg,Austria

2. School of Computing Science, University of Glasgow,Glasgow,United Kingdom

3. Stanford University,Department of Mathematics,Palo Alto,USA

4. School of Computer Science, Georgia Tech,Atlanta,USA

5. University of Illinois at Chicago,Computer Science Department,Chicago,USA

Funder

Austrian Science Fund

University of Toronto

Department of Defense

National Science Foundation

University of Illinois at Chicago

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9719594/9719683/09719829.pdf?arnumber=9719829

Reference94 articles.

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2. Input sparsity time low-rank approximation via ridge leverage score sampling;cohen;Proceedings of the 5th Annual ACM-SIAM Symposium on Discrete Algorithms,2017

3. Uniform Sampling for Matrix Approximation

4. L p Row Sampling by Lewis Weights

5. Graph minors for preserving terminal distances approximately - lower and upper bounds;cheung;43rd International Colloquium on Automata Languages and Programming ICALP 2016,2016

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