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  2. MurmurHash - Wikipedia

    en.wikipedia.org/wiki/MurmurHash

    MurmurHash is a non-cryptographic hash function suitable for general hash-based lookup. [1] [2] [3] It was created by Austin Appleby in 2008 [4] and, as of 8 January 2016, [5] is hosted on GitHub along with its test suite named SMHasher. It also exists in a number of variants, [6] all of which have been released into the public domain. The name ...

  3. Vowpal Wabbit - Wikipedia

    en.wikipedia.org/wiki/Vowpal_Wabbit

    Vowpal Wabbit (VW) is an open-source fast online interactive machine learning system library and program developed originally at Yahoo! Research , and currently at Microsoft Research . It was started and is led by John Langford .

  4. Whirlpool (hash function) - Wikipedia

    en.wikipedia.org/wiki/Whirlpool_(hash_function)

    In computer science and cryptography, Whirlpool (sometimes styled WHIRLPOOL) is a cryptographic hash function. It was designed by Vincent Rijmen (co-creator of the Advanced Encryption Standard) and Paulo S. L. M. Barreto, who first described it in 2000. The hash has been recommended by the NESSIE project.

  5. List of hash functions - Wikipedia

    en.wikipedia.org/wiki/List_of_hash_functions

    hash HAS-160: 160 bits hash HAVAL: 128 to 256 bits hash JH: 224 to 512 bits hash LSH [19] 256 to 512 bits wide-pipe Merkle–Damgård construction: MD2: 128 bits hash MD4: 128 bits hash MD5: 128 bits Merkle–Damgård construction: MD6: up to 512 bits Merkle tree NLFSR (it is also a keyed hash function) RadioGatún: arbitrary ideal mangling ...

  6. Hash function - Wikipedia

    en.wikipedia.org/wiki/Hash_function

    A hash function that allows only certain table sizes or strings only up to a certain length, or cannot accept a seed (i.e. allow double hashing) is less useful than one that does. [citation needed] A hash function is applicable in a variety of situations. Particularly within cryptography, notable applications include: [8]

  7. Locality-sensitive hashing - Wikipedia

    en.wikipedia.org/wiki/Locality-sensitive_hashing

    In computer science, locality-sensitive hashing (LSH) is a fuzzy hashing technique that hashes similar input items into the same "buckets" with high probability. [1] ( The number of buckets is much smaller than the universe of possible input items.) [1] Since similar items end up in the same buckets, this technique can be used for data clustering and nearest neighbor search.

  8. RIPEMD - Wikipedia

    en.wikipedia.org/wiki/RIPEMD

    RIPEMD (RIPE Message Digest) is a family of cryptographic hash functions developed in 1992 (the original RIPEMD) and 1996 (other variants). There are five functions in the family: RIPEMD, RIPEMD-128, RIPEMD-160, RIPEMD-256, and RIPEMD-320, of which RIPEMD-160 is the most common.

  9. Fowler–Noll–Vo hash function - Wikipedia

    en.wikipedia.org/wiki/Fowler–Noll–Vo_hash...

    Fowler–Noll–Vo (or FNV) is a non-cryptographic hash function created by Glenn Fowler, Landon Curt Noll, and Kiem-Phong Vo.. The basis of the FNV hash algorithm was taken from an idea sent as reviewer comments to the IEEE POSIX P1003.2 committee by Glenn Fowler and Phong Vo in 1991.