| Spectral norm of random matrices |
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Annual ACM Symposium on Theory of Computing
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Proceedings of the thirty-seventh annual ACM symposium on Theory of computing
table of contents
Baltimore, MD, USA
SESSION: Session 9B
table of contents
Pages: 423 - 430
Year of Publication: 2005
ISBN:1-58113-960-8
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Downloads (6 Weeks): 28, Downloads (12 Months): 93, Citation Count: 3
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ABSTRACT
In this paper, we present a new upper bound for the spectral norm of symmetric random matrices with independent (but not necessarily identical) entries. Our results improve an earlier result of Füredi and Komlós and also correct an incomplete argument in their proof.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
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N. Alon, M. Krivelevich and V. Vu, On the concentration of eigenvalues of random symmetric matrices, Israel J. Math.131 (2002), 259--267.
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FK Z, Füredi and J. Komlós, The eigenvalues of random symmetric matrices, Combinatorica 1 (1981), no. 3, 233--241.
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M. Krivelevich and V. Vu, Approximating the independence number and the chromatic number in expected polynomial time, J. Comb. Optim. 6 (2002), no. 2, 143--155.
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M. L. Mehta, Random matrices, Second edition. Academic Press, Inc., Boston, MA, 1991.
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Y. Sinai and A. Soshnikov, A Refinement of Wigner's Semicircle Law in a Neighborhood of the Spectrum edge, |it Functional Analysis and its Applications, 32 (1998) , No.2, pp.114--131.
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E. Wigner, On the distribution of the roots of certain symmetric matrices, The Annals of Mathematics 67 (1958) 325--327.
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CITED BY 3
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Anirban Dasgupta , John Hopcroft , Ravi Kannan , Pradipta Mitra, Spectral clustering with limited independence, Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms, p.1036-1045, January 07-09, 2007, New Orleans, Louisiana
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