Redundancy Reduction

Redundancy Reduction is a computational method that belongs to the class of content optimization techniques, distinguished by its specific function of minimizing repetitive or duplicative elements in generated outputs while preserving informational completeness and relevance within recommendation, error correction, pattern evaluation, and text summarization systems.

245

Publications

26K

Citations

729

Authors

303

Institutions

Publications per year

2017–2026

69

Authors

729

  1. GD
    Gustavo Deco

    Universitat Pompeu Fabra, Spain

    7 publications · 172 citations

    7

    h-index

  2. NP
    Néstor Parga

    Universidad Autónoma de Madrid, Spain

    5 publications · 481 citations

    5

    h-index

  3. JN
    Jean‐Pierre Nadal

    Centre National de la Recherche Scientifique, France

    5 publications · 481 citations

    5

    h-index

  4. MB
    Matthias Bethge

    University of Tübingen, Germany

    4 publications · 131 citations

    4

    h-index

  5. AR
    Amanda Redlich

    Institute for Advanced Study, United States

    4 publications · 913 citations

    4

    h-index

1–5 of 729

Venues

  1. Neural Computation

    10 publications · 10.4K citations

    10

    h-index

  2. arXiv (Cornell University)

    Repository · 9 publications · 1.4K citations

    9

    h-index

  3. Network Computation in Neural Systems

    8 publications · 1.2K citations

    8

    h-index

  4. IEEE Transactions on Image Processing

    6 publications · 2K citations

    6

    h-index

  5. 5

    h-index

1–5