Computer-readable recording medium recording estimation program, estimation method, and information processing device

Patent metadata

Field	Value
Publication number	US-2020042876-A1
Application number	US-201916653236-A
Country	US
Kind code	A1
Filing date	Oct 15, 2019
Priority date	May 16, 2017
Publication date	Feb 6, 2020
Grant date	—

Abstract

A non-transitory computer-readable recording medium records an estimation program causing a computer to execute processing which includes: calculating a reconfiguration error from an input result value and a reconfiguration value that is estimated by a first estimator, which estimates a parameter value from a result value learned on a basis of past data, and a second estimator, which estimates a result value from a parameter value, by using a specific result value or a neighborhood result value in a neighborhood of the specific result value; searching for a first result value that minimizes a sum of a substitute error that is calculated from the input result value and the specific result value and the reconfiguration error; and outputting a parameter value that is estimated from the first result value by using the first estimator.

First claim

What is claimed is:

1 . A non-transitory computer-readable recording medium recording an estimation program causing a computer to execute processing, the processing comprising:
calculating a reconfiguration error from an input result value and a reconfiguration value that is estimated by a first estimator, which estimates a parameter value from a result value learned on a basis of past data, and a second estimator, which estimates a result value from a parameter value, by using a specific result value or a neighborhood result value in a neighborhood of the specific result value; searching for a first result value that minimizes a sum of a substitute error that is calculated from the input result value and the specific result value and the reconfiguration error; and outputting a parameter value that is estimated from the first result value by using the first estimator.

2 . The non-transitory computer-readable recording medium according to claim 1 , wherein in a case where a total number of the past data is less than or equal to a threshold value, a weight of the reconfiguration error is calculated to be smaller than a weight of the substitute error when the sum is calculated.

3 . The non-transitory computer-readable recording medium according to claim 1 , wherein in a case where the first estimator and the second estimator are an estimator that uses a neural network, the neighborhood result value in the neighborhood of the specific result value is searched for by using a gradient of a total error that is the sum of the reconfiguration error and the substitute error in the searching.

4 . An estimation method comprising:
calculating, by a computer, a reconfiguration error from an input result value and a reconfiguration value that is estimated by a first estimator, which estimates a parameter value from a result value learned on a basis of past data, and a second estimator, which estimates a result value from a parameter value, by using a specific result value or a neighborhood result value in a neighborhood of the specific result value; searching for a first result value that minimizes a sum of a substitute error that is calculated from the input result value and the specific result value and the reconfiguration error; and outputting a parameter value that is estimated from the first result value by using the first estimator.

5 . The estimation method according to claim 4 , wherein in a case where a total number of the past data is less than or equal to a threshold value, a weight of the reconfiguration error is calculated to be smaller than a weight of the substitute error when the sum is calculated.

6 . The estimation method according to claim 4 , wherein in a case where the first estimator and the second estimator are an estimator that uses a neural network, the neighborhood result value in the neighborhood of the specific result value is searched for by using a gradient of a total error that is the sum of the reconfiguration error and the substitute error in the searching.

7 . An information processing device comprising:
a memory; and a processor coupled to the memory and configured to: calculate a reconfiguration error from an input result value and a reconfiguration value that is estimated by a first estimator, which estimates a parameter value from a result value learned on a basis of past data, and a second estimator, which estimates a result value from a parameter value, by using a specific result value or a neighborhood result value in a neighborhood of the specific result value; search for a first result value that minimizes a sum of a substitute error that is calculated from the input result value and the specific result value and the reconfiguration error; and output a parameter value that is estimated from the first result value by using the first estimator.

8 . The information processing device according to claim 7 , wherein in a case where a total number of the past data is less than or equal to a threshold value, a weight of the reconfiguration error is calculated to be smaller than a weight of the substitute error when the sum is calculated.

9 . The information processing device according to claim 7 , wherein in a case where the first estimator and the second estimator are an estimator that uses a neural network, the neighborhood result value in the neighborhood of the specific result value is searched for by using a gradient of a total error that is the sum of the reconfiguration error and the substitute error in the searching.

Assignees

• Fujitsu Ltd

Inventors

• Katoh Takashi
• UEMURA Kento
• Yasutomi Suguru
• Endoh Toshio
• Maruhashi Koji

Classifications

• G06N3/088 Primary

  Non-supervised learning, e.g. competitive learning · CPC title

• G06N3/08 Primary

  Learning methods · CPC title

• G06F18/214

  Generating training patterns; Bootstrap methods, e.g. bagging or boosting · CPC title

• G06N3/045

  Combinations of networks · CPC title

• G05B23/0281

  Quantitative, e.g. mathematical distance; Clustering; Neural networks; Statistical analysis · CPC title