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:
Jun. 21, 2022

Filed:

May. 15, 2017
Applicant:

International Business Machines Corporation, Armonk, NY (US);

Inventors:

Michael J. Witbrock, Ossining, NY (US);

Lingfei Wu, Croton on Hudson, NY (US);

Cao Xiao, White Plains, NY (US);

Jinfeng Yi, Ossining, NY (US);

Attorneys:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06K 9/62 (2022.01); G06N 20/00 (2019.01); G06F 15/76 (2006.01); G06N 20/10 (2019.01); G06N 7/00 (2006.01); G06N 5/00 (2006.01); G06N 3/08 (2006.01); G06N 3/04 (2006.01);
U.S. Cl.
CPC ...
G06K 9/6278 (2013.01); G06F 15/76 (2013.01); G06K 9/6256 (2013.01); G06K 9/6269 (2013.01); G06N 20/00 (2019.01); G06N 20/10 (2019.01); G06N 3/0454 (2013.01); G06N 3/0472 (2013.01); G06N 3/088 (2013.01); G06N 5/003 (2013.01); G06N 7/005 (2013.01);
Abstract

Embodiments of the present invention provide a computer-implemented method for performing unsupervised time-series feature learning. The method generates a set of reference time-series of random lengths, in which each length is uniformly sampled from a predetermined minimum length to a predetermined maximum length, and in which values of each reference time-series in the set are drawn from a distribution. The method generates a feature matrix for raw time-series data based on a set of computed distances between the generated set of reference time-series and the raw time-series data. The method provides the feature matrix as an input to one or more machine learning models.


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