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Patent Searching and Data


Title:
LEARNING SYSTEM, METHOD AND PROGRAM
Document Type and Number:
WIPO Patent Application WO/2020/202594
Kind Code:
A1
Abstract:
A classifier model learning unit 81 learns, using an input data, a classifier model for a mixture of classifiers referred as experts that are collectively assigned to a task of classification of the input data, at each time instance. A classifier time series model learning unit 82 learns, for each expert, a time series model indicating time series change of the classifier model of the expert. A data model parameter learning unit 83 learns a data model parameter for a data model indicating the distribution of data features for each expert. An assignment parameter learning unit 84 learns an assignment parameter indicating the probability of assigning experts for each expert.

Inventors:
DHAKA DEVENDRA (JP)
KHANDELWAL KANISHKA (JP)
ETO RIKI (JP)
Application Number:
PCT/JP2019/029456
Publication Date:
October 08, 2020
Filing Date:
July 26, 2019
Export Citation:
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Assignee:
NEC CORP (JP)
International Classes:
G06N20/00
Foreign References:
JP2006127446A2006-05-18
US20190041235A12019-02-07
JP2017107386A2017-06-15
Other References:
SASAKI, KENTARO ET AL.: "Time Series Topic Model Considering Dependence to Multiple Topics", IPSJ SIG TECHNICAL REPORTS. MPS-100, vol. 2014, no. 3, 18 September 2014 (2014-09-18), pages 1 - 6, XP055745989, Retrieved from the Internet [retrieved on 20190827]
KOIZUMI, YUMA ET AL.: "Intra-note Segmentation for Excitation- Continuous Musical Instruments based on Infinite Mixture Models nesting Hidden Markov Model", PROCEEDINGS OF 2014 SPRING MEETING OF ACOUSTICAL SOCIETY OF JAPAN [ CD-ROM), 3 March 2014 (2014-03-03), pages 985 - 988, ISSN: 1880-7658
ATTAMIMI, MUHAMMAD ET AL.: "Autonomous Control of a Service Robot Based on Remote Control Data", PROCEEDINGS OF THE 31ST ANNUAL CONFERENCE OF THE ROBOTICS SOCIETY OF JAPAN [ DVD -ROM), RSJ2013AC2C2-04, 4 September 2013 (2013-09-04)
HANNAH, LAUREN A ET AL.: "Dirichlet Process Mixtures of Generalized Linear Models", JOURNAL OF MACHINE LEARNING RESEARCH, vol. 12, 2011, pages 1923 - 1953, XP055745980
Attorney, Agent or Firm:
IWAKABE Fuyuki et al. (JP)
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