Pith. sign in

REVIEW 1 cited by

Lectures on Randomized Numerical Linear Algebra

Not yet reviewed by Pith; the record is open.

Re-run · record.json Download PDF Read on arXiv ↗

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 1712.08880 v1 pith:EYNIGTRI submitted 2017-12-24 cs.DS stat.ML

Lectures on Randomized Numerical Linear Algebra

Petros Drineas , Michael W. Mahoney This is my paper
classification cs.DS stat.ML
keywords algebralectureslinearmathematicsnumericalrandomizedchaptercity
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
0 comments
read the original abstract

This chapter is based on lectures on Randomized Numerical Linear Algebra from the 2016 Park City Mathematics Institute summer school on The Mathematics of Data.

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Improved large-scale graph learning through ridge spectral sparsification

    cs.LG 2026-04 unverdicted novelty 5.0

    GSQUEAK produces spectrally accurate sparsifiers for graph Laplacians in a single-pass distributed streaming setting.