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Scaling machine learning using approximate counting

  • US 8,255,343 B1
  • Filed: 08/09/2011
  • Issued: 08/28/2012
  • Est. Priority Date: 05/16/2007
  • Status: Active Grant
First Claim
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1. A method performed by one or more of a plurality of computer devices, the method comprising:

  • identifying, by a first computer device of the plurality of computer devices, a feature set that includes at least a first feature and a second feature;

    storing, by the first computer device and in a plurality of memory locations in a memory, values relating to the first feature;

    subjecting, by the first computer device, a string, associated with the first feature, to multiple, different hash functions to generate multiple, different hash values;

    identifying, by the first computer device, for each of the multiple, different hash values, a respective memory location, of the plurality of memory locations in the memory;

    reading, by the first computer device, the values stored at the respective memory locations;

    performing, by the first computer device, an operation on the read values from the respective memory locations to obtain updated values;

    writing, by the first computer device, the updated values into the respective memory locations;

    sending, by the first computer device, a request to a second computer device, of the plurality of computer devices, for information regarding the second feature;

    receiving, by the first computer device, the information from the second computer device; and

    using, by the first computer device, the updated values and the received information to make a prediction regarding particular data.

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