Change-point detection in a sequence of bags-of-data

Kensuke Koshijima, Hideitsu Hino, Noboru Murata

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

In this paper, the limitation that is prominent in most existing works of change-point detection methods is addressed by proposing a nonparametric, computationally efficient method. The limitation is that most works assume that each data point observed at each time step is a single multi-dimensional vector. However, there are many situations where this does not hold. Therefore, a setting where each observation is a collection of random variables, which we call a bag of data, is considered.

Original languageEnglish
Title of host publication2016 IEEE 32nd International Conference on Data Engineering, ICDE 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1560-1561
Number of pages2
ISBN (Electronic)9781509020195
DOIs
Publication statusPublished - 2016 Jun 22
Event32nd IEEE International Conference on Data Engineering, ICDE 2016 - Helsinki, Finland
Duration: 2016 May 162016 May 20

Publication series

Name2016 IEEE 32nd International Conference on Data Engineering, ICDE 2016

Other

Other32nd IEEE International Conference on Data Engineering, ICDE 2016
CountryFinland
CityHelsinki
Period16/5/1616/5/20

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computational Theory and Mathematics
  • Computer Graphics and Computer-Aided Design
  • Computer Networks and Communications
  • Information Systems
  • Information Systems and Management

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