Listwise Ranking

Listwise Ranking is a learning-to-rank approach that treats ranking as a holistic prediction task by directly optimizing the entire list of ordered items as a single instance, thereby differing from pairwise or pointwise methods that decompose ranking into simpler classification or regression subproblems.

51

Publications

3.2K

Citations

182

Authors

74

Institutions

Publications per year

2017–2026

22

Authors

182

  1. FW
    Fei Wu

    Zhejiang University, China

    4 publications · 183 citations

    4

    h-index

  2. YZ
    Yueting Zhuang

    Zhejiang University, China

    4 publications · 183 citations

    4

    h-index

  3. ZZ
    Zhongfei Zhang

    Binghamton University, United States

    3 publications · 170 citations

    3

    h-index

  4. XL
    Xinyan Lu

    Chinese Academy of Sciences, China

    3 publications · 146 citations

    3

    h-index

  5. YL
    Yanyan Lan

    Chinese Academy of Sciences, China

    3 publications · 83 citations

    3

    h-index

1–5 of 182

Venues

  1. arXiv (Cornell University)

    Repository · 4 publications · 72 citations

    4

    h-index

  2. Neural Information Processing Systems

    Conference · 2 publications · 28 citations

    2

    h-index

  3. IEEE Transactions on Image Processing

    2 publications · 802 citations

    2

    h-index

  4. PLoS ONE

    1 publications · 14 citations

    1

    h-index

  5. Journal of Computational Science

    1 publications · 14 citations

    1

    h-index

1–5