Sparse Word Embeddings

Sparse Word Embeddings is a type of word embedding representation in which the majority of the elements in the vector are zero or near-zero, thereby emphasizing a compact and often interpretable encoding of linguistic features through sparsity-inducing constraints.

128

Publications

42.3K

Citations

409

Authors

178

Institutions

Publications per year

2017–2026

87

Authors

409

  1. HS
    Hinrich Schütze

    Ludwig-Maximilians-Universität München, Germany

    3 publications · 197 citations

    3

    h-index

  2. SR
    Sascha Rothe

    Ludwig-Maximilians-Universität München, Germany

    3 publications · 343 citations

    3

    h-index

  3. ZM
    Zongyang Ma

    Nanyang Technological University, Singapore

    2 publications · 443 citations

    2

    h-index

  4. QY
    Qian Yang

    Xihua University, China

    2 publications · 23 citations

    2

    h-index

  5. ZZ
    Zhiqian Zhang

    Institute of High Performance Computing, Singapore

    2 publications · 443 citations

    2

    h-index

1–5 of 409

Venues

  1. arXiv (Cornell University)

    Repository · 15 publications · 611 citations

    12

    h-index

  2. Journal of Biomedical Informatics

    3 publications · 428 citations

    3

    h-index

  3. World Wide Web

    2 publications · 40 citations

    2

    h-index

  4. Neural Information Processing Systems

    Conference · 2 publications · 1.6K citations

    2

    h-index

  5. 2

    h-index

1–5