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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.

Patent No.:

US 11455284 B1

PDFFull Text
Date of Patent:
Sep. 27, 2022

Filed:

Sep. 09, 2019

Method and system for adaptively imputing sparse and missing data for predictive models

Applicant:

Oracle International Corporation, Redwood Shores, CA (US);

Inventors:

Michael Zoll, Foster City, CA (US);

Yaser I. Suleiman, Santa Clara, CA (US);

Subhransu Basu, Fremont, CA (US);

Angelo Pruscino, Los Altos, CA (US);

Wolfgang Lohwasser, Munich, DE;

Wataru Miyoshi, Redwood City, CA (US);

Thomas Breidt, Munich, DE;

Thomas Herter, Santa Clara, CA (US);

Klaus Thielen, Munich, DE;

Sahil Kumar, Redwood City, CA (US);

Assignee:

Oracle International Corporation;

Attorney:

Vista IP Law Group, LLP

Primary Examiner:

Mahesh H Dwivedi

Int. Cl.
CPC ...
G06F 16/30 (2019.01); G06F 16/215 (2019.01); G06K 9/62 (2022.01); G06F 11/34 (2006.01); G06N 20/20 (2019.01); H04L 41/142 (2022.01); G06N 7/00 (2006.01); H04L 41/069 (2022.01); G06N 20/00 (2019.01); H04L 41/0695 (2022.01); H04L 41/0823 (2022.01); H04L 43/02 (2022.01);
U.S. Cl.
CPC ...
G06F 16/215 (2019.01); G06F 11/3409 (2013.01); G06F 11/3452 (2013.01); G06K 9/6256 (2013.01); G06N 7/005 (2013.01); G06N 20/20 (2019.01); H04L 41/069 (2013.01); H04L 41/142 (2013.01); G06N 20/00 (2019.01); H04L 41/0695 (2013.01); H04L 41/0823 (2013.01); H04L 43/02 (2013.01);
Abstract

Described is an approach that provides an adaptive solution to missing data for machine learning systems. A gradient solution is provided that is attentive to imputation needs at each of several missingness levels. This multilevel approach treats data missingness at any of multiple severity levels while utilizing, as much as possible, the actual observed data.

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