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Ethan N. Epperly

University of California, Berkeley

28 papers hereh-index 12447 citations36 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • sole author4
  • first author11
  • middle author13

Across the 28 of 28 papers where every author was matched, so the position is known.

fields
  • math.NA19
  • cs.DS4
  • quant-ph2
  • cs.IT1
  • math.OC1
  • stat.ML1
affiliations
  • University of California, Berkeley
Homepage

identity via Semantic Scholar / OpenAlex

activity
20192026
most citedA theory of quantum subspace diagonalization

67 citations · 107 across the 27 of their papers we have counts for

collaborators
Showing cs.DSShow all

4 papers · 1 filter

cs.DS2026

Fast Length-Squared Sampling for Positive-Semidefinite Matrices

Rajarshi Bhattacharjee, Ethan N. Epperly, Cameron Musco +1

We describe a simple rejection-sampling-based algorithm to perform length-squared sampling on an n×n positive-semidefinite (psd) matrix: that is, to sample a column with p…

cs.DS2026

The matrix-vector complexity of Ax=b

Michał Dereziński, Ethan N. Epperly, Raphael A. Meyer

Matrix--vector algorithms, particularly Krylov subspace methods, are widely viewed as the most effective algorithms for solving large systems of linear equations. This paper establ…

cs.DS2025

Faster Linear Algebra Algorithms with Structured Random Matrices

Chris Camaño, Ethan N. Epperly, Raphael A. Meyer +1

To achieve the greatest possible speed, practitioners regularly implement randomized algorithms for low-rank approximation and least-squares regression with structured dimension re…

cs.DS2025

Does block size matter in randomized block Krylov low-rank approximation?

Tyler Chen, Ethan N. Epperly, Raphael A. Meyer +2

We study the problem of computing a rank-k approximation of a matrix using randomized block Krylov iteration. Prior work has shown that, for block size b=1 or b=k, a $(1…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.