Inner Product Function

The Inner Product Function is a fundamental boolean function in communication complexity that computes the parity of the bitwise dot product of two binary input vectors, distinguishing itself from other boolean functions by its reliance on modular arithmetic over the finite field GF(2) to determine output.

242

Publications

11.5K

Citations

447

Authors

249

Institutions

Publications per year

2017–2026

33

Variants

Ip Function

Authors

447

  1. JE
    Joseph E. Pasciak

    Texas A&M University, United States

    3 publications · 295 citations

    3

    h-index

  2. JH
    James H. Bramble

    Cornell University, United States

    3 publications · 295 citations

    3

    h-index

  3. AK
    Alexander Kirillov

    Yale University, United States

    2 publications · 54 citations

    2

    h-index

  4. PE
    Pavel Etingof

    Massachusetts Institute of Technology, United States

    2 publications · 54 citations

    2

    h-index

  5. HF
    Hakan Ferhatosmanoğlu

    The Ohio State University, United States

    2 publications · 73 citations

    2

    h-index

1–5 of 447

Venues

  1. Pacific Journal of Mathematics

    7 publications · 366 citations

    7

    h-index

  2. arXiv (Cornell University)

    Repository · 5 publications · 491 citations

    5

    h-index

  3. ArXiv.org

    Repository · 4 publications · 138 citations

    4

    h-index

  4. Bulletin of the American Mathematical Society

    4 publications · 563 citations

    4

    h-index

  5. Illinois Journal of Mathematics

    IJM · 4 publications · 62 citations

    4

    h-index

1–5