Metric Compression

Metric Compression is a computational method within the domain of metrics collection that reduces the dimensionality or volume of collected metrics while preserving essential information for analysis.

41

Publications

2K

Citations

101

Authors

59

Institutions

Publications per year

2017–2026

11

Authors

101

  1. SK
    Suresh K. Lodha

    University of California, Santa Cruz, United States

    2 publications · 72 citations

    2

    h-index

  2. AN
    Assaf Naor

    Courant Institute of Mathematical Sciences, United States

    2 publications · 38 citations

    2

    h-index

  3. JC
    Jose C. Renteria

    University of California, Santa Cruz, United States

    2 publications · 72 citations

    2

    h-index

  4. IN
    Ilan Newman

    University of Haifa, Israel

    2 publications · 60 citations

    2

    h-index

  5. PV
    Paul Vitányi

    Centrum Wiskunde & Informatica, Netherlands

    2 publications · 82 citations

    2

    h-index

1–5 of 101

Venues

  1. 2

    h-index

  2. Computers & Graphics

    1 publications · 34 citations

    1

    h-index

  3. Pattern Recognition

    1 publications · 16 citations

    1

    h-index

  4. IEEE Transactions on Information Theory

    1 publications · 36 citations

    1

    h-index

  5. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 1 publications · 21 citations

    1

    h-index

1–5