Corpus ID: 504577

Change-Point Detection with Feature Selection in High-Dimensional Time-Series Data

@inproceedings{Yamada2013ChangePointDW,
  title={Change-Point Detection with Feature Selection in High-Dimensional Time-Series Data},
  author={M. Yamada and A. Kimura and F. Naya and H. Sawada},
  booktitle={IJCAI},
  year={2013}
}
  • M. Yamada, A. Kimura, +1 author H. Sawada
  • Published in IJCAI 2013
  • Mathematics, Computer Science
  • Change-point detection is the problem of finding abrupt changes in time-series, and it is attracting a lot of attention in the artificial intelligence and data mining communities. [...] Key Method Here, the HSIC is a kernel-based independence measure. A novel aspect of the aHSIC score is that it can incorporate feature selection during its detection measure estimation.Expand Abstract
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