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Mapping the Similarities of Spectra: Global and Locally-biased
  Approaches to SDSS Galaxy Data

Mapping the Similarities of Spectra: Global and Locally-biased Approaches to SDSS Galaxy Data

13 September 2016
David Lawlor
T. Budavári
Michael W. Mahoney
ArXivPDFHTML

Papers citing "Mapping the Similarities of Spectra: Global and Locally-biased Approaches to SDSS Galaxy Data"

3 / 3 papers shown
Title
Strongly local p-norm-cut algorithms for semi-supervised learning and
  local graph clustering
Strongly local p-norm-cut algorithms for semi-supervised learning and local graph clustering
Meng Liu
D. Gleich
16
13
0
15 Jun 2020
Flow-based Algorithms for Improving Clusters: A Unifying Framework,
  Software, and Performance
Flow-based Algorithms for Improving Clusters: A Unifying Framework, Software, and Performance
K. Fountoulakis
M. Liu
D. Gleich
Michael W. Mahoney
29
11
0
20 Apr 2020
Improved guarantees and a multiple-descent curve for Column Subset
  Selection and the Nyström method
Improved guarantees and a multiple-descent curve for Column Subset Selection and the Nyström method
Michal Derezinski
Rajiv Khanna
Michael W. Mahoney
31
10
0
21 Feb 2020
1