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:
Nov. 12, 2019

Filed:

Jun. 29, 2015
Applicant:

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

Inventors:

Xiaodong He, Sammamish, WA (US);

Jianshu Chen, Redmond, WA (US);

Brendan W L Clement, Redmond, WA (US);

Li Deng, Redmond, WA (US);

Jianfeng Gao, Woodinville, WA (US);

Bochen Jin, Bellevue, WA (US);

Prabhdeep Singh, Newcastle, WA (US);

Sandeep P. Solanki, Redmond, WA (US);

LuMing Wang, Bellevue, WA (US);

Hanjun Xian, Redmond, WA (US);

Yilei Zhang, Kirkland, WA (US);

Mingyang Zhao, Issaquah, WA (US);

Zijian Zheng, Bellevue, WA (US);

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06N 3/08 (2006.01); G06N 20/00 (2019.01); G06N 3/04 (2006.01);
U.S. Cl.
CPC ...
G06N 3/08 (2013.01); G06N 3/049 (2013.01); G06N 3/0454 (2013.01); G06N 20/00 (2019.01);
Abstract

A processing unit can acquire datasets from respective data sources, each having a respective unique data domain. The processing unit can determine values of a plurality of features based on the plurality of datasets. The processing unit can modify input-specific parameters or history parameters of a computational model based on the values of the features. In some examples, the processing unit can determine an estimated value of a target feature based at least in part on the modified computational model and values of one or more reference features. In some examples, the computational model can include neural networks for several input sets. An output layer of at least one of the neural networks can be connected to the respective hidden layer(s) of one or more other(s) of the neural networks. In some examples, the neural networks can be operated to provide transformed feature value(s) for respective times.


Find Patent Forward Citations

Loading…