enow.com Web Search

Search results

  1. Results from the WOW.Com Content Network
  2. Count sketch - Wikipedia

    en.wikipedia.org/wiki/Count_Sketch

    Count sketch is a type of dimensionality reduction that is particularly efficient in statistics, machine learning and algorithms. [1] [2] It was invented by Moses Charikar, Kevin Chen and Martin Farach-Colton [3] in an effort to speed up the AMS Sketch by Alon, Matias and Szegedy for approximating the frequency moments of streams [4] (these calculations require counting of the number of ...

  3. Count–min sketch - Wikipedia

    en.wikipedia.org/wiki/Count–min_sketch

    The count–min sketch was invented in 2003 by Graham Cormode and S. Muthu Muthukrishnan [1] and described by them in a 2005 paper. [2] Count–min sketch is an alternative to count sketch and AMS sketch and can be considered an implementation of a counting Bloom filter (Fan et al., 1998 [3]) or multistage-filter. [1]

  4. HyperLogLog - Wikipedia

    en.wikipedia.org/wiki/HyperLogLog

    The HyperLogLog has three main operations: add to add a new element to the set, count to obtain the cardinality of the set and merge to obtain the union of two sets. Some derived operations can be computed using the inclusion–exclusion principle like the cardinality of the intersection or the cardinality of the difference between two HyperLogLogs combining the merge and count operations.

  5. Streaming algorithm - Wikipedia

    en.wikipedia.org/wiki/Streaming_algorithm

    The first moment is simply the sum of the frequencies (i.e., the total count). The second moment F 2 {\displaystyle F_{2}} is useful for computing statistical properties of the data, such as the Gini coefficient of variation.

  6. Tensor sketch - Wikipedia

    en.wikipedia.org/wiki/Tensor_sketch

    In statistics, machine learning and algorithms, a tensor sketch is a type of dimensionality reduction that is particularly efficient when applied to vectors that have tensor structure. [ 1 ] [ 2 ] Such a sketch can be used to speed up explicit kernel methods , bilinear pooling in neural networks and is a cornerstone in many numerical linear ...

  7. Flajolet–Martin algorithm - Wikipedia

    en.wikipedia.org/wiki/Flajolet–Martin_algorithm

    The Flajolet–Martin algorithm is an algorithm for approximating the number of distinct elements in a stream with a single pass and space-consumption logarithmic in the maximal number of possible distinct elements in the stream (the count-distinct problem).

  8. AOL Mail

    mail.aol.com/d?reason=invalid_cred

    Get AOL Mail for FREE! Manage your email like never before with travel, photo & document views. Personalize your inbox with themes & tabs. You've Got Mail!

  9. Count-distinct problem - Wikipedia

    en.wikipedia.org/wiki/Count-distinct_problem

    There are other estimation techniques other than min/max sketches. The first paper on count-distinct estimation [7] describes the Flajolet–Martin algorithm, a bit pattern sketch. In this case, the elements are hashed into a bit vector and the sketch holds the logical OR of all hashed values.