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Matrix discrepancy and the log-rank conjecture
ETH Zurich, Zürich, Switzerland.
Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.ORCID iD: 0000-0001-8344-3592
2024 (English)In: Mathematical programming, ISSN 0025-5610, E-ISSN 1436-4646Article in journal (Refereed) Epub ahead of print
Abstract [en]

Given an m×n binary matrix M with |M|=p·mn (where |M| denotes the number of 1 entries), define the discrepancy of M as disc(M)=maxX⊂[m],Y⊂[n]||M[X×Y]|-p|X|·|Y||. Using semidefinite programming and spectral techniques, we prove that if rank(M)≤r and p≤1/2, then (Formula presented.) We use this result to obtain a modest improvement of Lovett’s best known upper bound on the log-rank conjecture. We prove that any m×n binary matrix M of rank at most r contains an (m·2-O(r))×(n·2-O(r)) sized all-1 or all-0 submatrix, which implies that the deterministic communication complexity of any Boolean function of rank r is at most O(r).

Place, publisher, year, edition, pages
2024.
Keywords [en]
68Q17, 68R05, Discrepancy, Log-rank conjecture
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:umu:diva-227883DOI: 10.1007/s10107-024-02117-9ISI: 001262894200002Scopus ID: 2-s2.0-85197710212OAI: oai:DiVA.org:umu-227883DiVA, id: diva2:1884177
Available from: 2024-07-15 Created: 2024-07-15 Last updated: 2025-04-24

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Tomon, István

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CiteExportLink to record
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