The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Dec. 07, 2021

Filed:

Jun. 30, 2018
Applicant:

Microsoft Technology Licensing, Llc, Redmond, WA (US);

Inventors:

Christopher Wright Lloyd, II, New York City, NY (US);

Konstantin Salomatin, San Francisco, CA (US);

Jeffrey Douglas Gee, San Francisco, CA (US);

Mahesh S. Joshi, Belmont, CA (US);

Shivani Rao, Mountain View, CA (US);

Vladislav Tcheprasov, Lafayette, CA (US);

Gungor Polatkan, San Jose, CA (US);

Deepak Kumar Dileep Kumar, Sunnyvale, CA (US);

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/00 (2006.01); G06N 20/00 (2019.01); G06K 9/62 (2006.01);
U.S. Cl.
CPC ...
G06K 9/00744 (2013.01); G06K 9/6228 (2013.01); G06K 9/6257 (2013.01); G06N 20/00 (2019.01);
Abstract

Techniques for implementing a feature generation pipeline for machine learning are provided. In one technique, multiple jobs are executed, each of which computes a different set of feature values for a different feature of multiple features associated with videos. A feature registry is stored that lists each of the multiple features. After the jobs are executed and the feature registry is stored, a model specification is received that indicates a set of features for a model. For each feature in a subset of the set of features, a location is identified in storage where a value for said each feature is found and the value for that feature is retrieved from the location. A feature vector is created that comprises, for each feature in the set of features, the value that corresponds to that feature. The feature vector is used to train the model or as input to the model.


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