Smoothness of Schatten norms and sliding-window matrix streams

Robert Krauthgamer, Shay Sapir

Research output: Contribution to journalArticlepeer-review

Abstract

Large matrices are often accessed as a row-order stream. We consider the setting where rows are time-sensitive (i.e. they expire), which can be described by the sliding-window row-order model, and provide the first (1+ϵ)-approximation of Schatten p-norms in this setting. Our main technical contribution is a proof that Schatten p-norms in row-order streams are smooth, and thus fit the smooth-histograms technique of Braverman and Ostrovsky (FOCS 2007) for sliding-window streams.

Original languageEnglish
Article number106254
JournalInformation Processing Letters
Volume177
DOIs
StatePublished - Aug 2022

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Information Systems
  • Signal Processing
  • Computer Science Applications

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