Vector Smoothing

Vector Smoothing is a computational method in vector modeling that refines high-dimensional vector representations by reducing noise and variability through weighted averaging or regularization techniques to enhance semantic coherence and representation stability.

12

Publications

404

Citations

30

Authors

16

Institutions

Publications per year

2017–2026

3

Authors

30

  1. JT
    Junichi Takahashi

    Fukushima University, Japan

    2 publications · 53 citations

    2

    h-index

  2. SS
    Shigeki Sagayama

    The University of Tokyo, Japan

    2 publications · 53 citations

    2

    h-index

  3. JE
    John E. Boylan

    Buckinghamshire New University, United Kingdom

    1 publications · 28 citations

    1

    h-index

  4. JT
    Jianwu Tao

    PLA Air Force Aviation University, China

    1 publications · 27 citations

    1

    h-index

  5. TS
    Ting Shu

    Shanghai Jiao Tong University, China

    1 publications · 13 citations

    1

    h-index

1–5 of 30

Venues

  1. AIAA Journal

    1 publications · 22 citations

    1

    h-index

  2. Journal of Information Processing Systems

    1 publications · 12 citations

    1

    h-index

  3. IEEE Sensors Letters

    1 publications · 13 citations

    1

    h-index

  4. Mathematical Geology

    1 publications · 13 citations

    1

    h-index

  5. 1

    h-index

1–5