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A Very Sketchy Talk (Invited Talk)

Author David P. Woodruff

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David P. Woodruff
  • Carnegie Mellon University, Pittsburgh, PA, USA

Funding

  • Woodruff, David P.: Supported by the Office of Naval Research (ONR) grant N00014-18-1-2562, the National Science Foundation (NSF) under Grant No. CCF-1815840, and a Simons Investigator Award.

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David P. Woodruff. A Very Sketchy Talk (Invited Talk). In 48th International Colloquium on Automata, Languages, and Programming (ICALP 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 198, pp. 6:1-6:8, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)
https://doi.org/10.4230/LIPIcs.ICALP.2021.6

Abstract

We give an overview of dimensionality reduction methods, or sketching, for a number of problems in optimization, first surveying work using these methods for classical problems, which gives near optimal algorithms for regression, low rank approximation, and natural variants. We then survey recent work applying sketching to column subset selection, kernel methods, sublinear algorithms for structured matrices, tensors, trace estimation, and so on. The focus is on fast algorithms. This is a short survey accompanying an invited talk at ICALP, 2021.

Subject Classification

ACM Subject Classification
  • Theory of computation → Streaming, sublinear and near linear time algorithms
Keywords
  • dimensionality reduction
  • optimization
  • randomized numerical linear algebra
  • sketching

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References

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