Coreset Construction

Coreset Construction is a parameterized algorithmic technique that, within the broader class of data reduction methods, specifically involves the design of a weighted subset of data points—constructed to preserve key structural properties of the original dataset with respect to a given optimization problem, parameterized by solution quality and computational efficiency—thereby enabling scalable approximation algorithms in high-dimensional or large-scale settings.

116

Publications

6.5K

Citations

210

Authors

109

Institutions

Publications per year

2017–2026

56

Authors

210

  1. DF
    Dan Feldman

    University of Haifa, Israel

    20 publications · 1.4K citations

    16

    h-index

  2. CS
    Christian Sohler

    TU Dortmund University, Germany

    14 publications · 1.2K citations

    14

    h-index

  3. AK
    Andreas Krause

    ETH Zurich, Switzerland

    10 publications · 557 citations

    10

    h-index

  4. ML
    Mario Lučić

    Google (United States), United States

    7 publications · 364 citations

    7

    h-index

  5. TB
    Tamara Broderick

    University of California, Berkeley, United States

    5 publications · 227 citations

    5

    h-index

1–5 of 210

Venues

  1. arXiv (Cornell University)

    Repository · 26 publications · 938 citations

    16

    h-index

  2. DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)

    Repository · 3 publications · 122 citations

    3

    h-index

  3. Neural Information Processing Systems

    Conference · 3 publications · 124 citations

    3

    h-index

  4. Computational Geometry

    2 publications · 274 citations

    2

    h-index

  5. ACM Journal of Experimental Algorithmics

    JEA · 2 publications · 457 citations

    2

    h-index

1–5