Information-theoretic approximations of the nonnegative rank-Reference-Cited by-同舟云学术

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Information-theoretic approximations of the nonnegative rank

Published:2016-05-23 Issue:1 Volume:26 Page:147-197
ISSN:1016-3328
Container-title:computational complexity
language:en
Short-container-title:comput. complex.

Author:

Braun Gábor,Jain Rahul,Lee Troy,Pokutta Sebastian

Publisher

Springer Science and Business Media LLC

Subject

Computational Mathematics,Computational Theory and Mathematics,General Mathematics,Theoretical Computer Science

Link

http://link.springer.com/content/pdf/10.1007/s00037-016-0125-z.pdf

Reference26 articles.

1. Z. Bar-Yossef, T.S. Jayram, R. Kumar & D. Sivakumar (2004). An information statistics approach to data stream and communication complexity. Journal of Computer and System Sciences 68(4), 702–732. http://www.sciencedirect.com/science/article/pii/S0022000003001855 .

2. B. Barak, M. Braverman, X. Chen & A. Rao (2010). How to compress interactive communication. In 42nd ACM Symposium on Theory of Computing, 67–76.

3. G. Braun & S. Pokutta (2013). Common information and unique disjointness. In Proceedings of the 54th IEEE Symposium on Foundations of Computer Science, 688–697.

4. G. Braun, S. Fiorini, S. Pokutta & D. Steurer (2012). Approximation limits of linear programs (beyond hierarchies). In 53rd IEEE Symposium on Foundations of Computer Science, 480–489. ISBN 978-1-4673-4383-1.

5. G. Braun, S. Pokutta & D. Zink (2015). Inapproximability of combinatorial problems via small LPs and SDPs. In Proceedings of the 47th Annual Symposium on the Theory of Computing, 107–116.

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2. Common Information, Noise Stability, and Their Extensions;Foundations and Trends® in Communications and Information Theory;2022

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4. On the Complexity of Some Facet-Defining Inequalities of the QAP-Polytope;Combinatorial Optimization and Applications;2020

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