Invention Grant
- Patent Title: Apparatus and method for learning a model corresponding to time-series input data
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Application No.: US15254378Application Date: 2016-09-01
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Publication No.: US10909451B2Publication Date: 2021-02-02
- Inventor: Takayuki Osogami
- Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
- Applicant Address: US NY Armonk
- Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
- Current Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
- Current Assignee Address: US NY Armonk
- Agency: Tutunjian & Bitetto, P.C.
- Agent Randall Bluestone
- Main IPC: G06N3/08
- IPC: G06N3/08 ; G06N3/04

Abstract:
A learning apparatus and method for learning a model corresponding to time-series input data, comprising: acquire the time-series input data; supply a plurality of input nodes of the model with a plurality of input values corresponding to input data at one time point in the time-series input data; store values of hidden nodes; compute a conditional probability of each input value at the one time point on a condition that an input data sequence has occurred, based on the input data sequence before the one time point in the time-series input data, on the stored values of hidden nodes, and on weight parameters; and perform a learning process that further increases a conditional probability of input data occurring at the one time point on the condition that the input data sequence has occurred, by adjusting the weight parameters.
Public/Granted literature
- US20180060729A1 APPARATUS AND METHOD FOR LEARNING A MODEL CORRESPONDING TO TIME-SERIES INPUT DATA Public/Granted day:2018-03-01
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