Norms of random matrices: Local and global problems

Elizaveta Rebrova, Roman Vershynin

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

Can the behavior of a random matrix be improved by modifying a small fraction of its entries? Consider a random matrix A with i.i.d. entries. We show that the operator norm of A can be reduced to the optimal order O(n) by zeroing out a small submatrix of A if and only if the entries have zero mean and finite variance. Moreover, we obtain an almost optimal dependence between the size of the removed submatrix and the resulting operator norm. Our approach utilizes the cut norm and Grothendieck–Pietsch factorization for matrices, and it combines the methods developed recently by C. Le and R. Vershynin and by E. Rebrova and K. Tikhomirov.

Original languageEnglish (US)
Pages (from-to)40-83
Number of pages44
JournalAdvances in Mathematics
Volume324
DOIs
StatePublished - Jan 14 2018
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Mathematics(all)

Keywords

  • Bai–Yin law
  • Heavy tails
  • Operator norm
  • Random matrices

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