We propose an efficient algorithm for principal component analysis (PCA) that is applicable when only the inner product with a given vector is needed. We show that Krylov subspace learning works well both in matrix compression and implicit calculation of the inner product by taking full advantage of the arbitrariness of the seed vector. We apply our algorithm to a PCA-based change-point detection algorithm, and show that it results in about 50 times improvement in computational time.
| Author(s): | Ide, T. and Tsuda, K. |
| Book Title: | SDM 2007 |
| Journal: | Proceedings of the SIAM International Conference on Data Mining (SDM 2007) |
| Pages: | 515-520 |
| Year: | 2007 |
| Month: | April |
| Day: | 0 |
| Editors: | Apte, C. |
| Publisher: | Society for Industrial and Applied Mathematics |
| Bibtex Type: | Conference Paper (inproceedings) |
| Address: | Pittsburgh, PA, USA |
| Event Name: | SIAM International Conference on Data Mining |
| Event Place: | Minneapolis, MN, USA |
| Digital: | 0 |
| Electronic Archiving: | grant_archive |
| Institution: | Society for Industrial and Applied Mathematics |
| Language: | en |
| Organization: | Max-Planck-Gesellschaft |
| School: | Biologische Kybernetik |
| Links: | |
BibTex
@inproceedings{4399,
title = {Change-Point Detection using Krylov Subspace Learning},
journal = {Proceedings of the SIAM International Conference on Data Mining (SDM 2007)},
booktitle = {SDM 2007},
abstract = {We propose an efficient algorithm for principal component analysis (PCA) that is applicable when only the inner product with a given vector is needed. We show that Krylov subspace learning works well both in matrix compression and implicit calculation of the inner product by taking full advantage of the arbitrariness of the seed vector. We apply our algorithm to a PCA-based change-point detection
algorithm, and show that it results in about 50 times improvement in computational time.},
pages = {515-520},
editors = {Apte, C. },
publisher = {Society for Industrial and Applied Mathematics},
organization = {Max-Planck-Gesellschaft},
institution = {Society for Industrial and Applied Mathematics},
school = {Biologische Kybernetik},
address = {Pittsburgh, PA, USA},
month = apr,
year = {2007},
slug = {4399},
author = {Ide, T. and Tsuda, K.},
month_numeric = {4}
}