講演抄録/キーワード |
講演名 |
2014-11-17 17:00
[ポスター講演]Importance-Weighted Covariance Estimation for Robust Common Spatial Pattern Alessandro Balzi(PoliMi)・○Florian Yger・Masashi Sugiyama(Univ. of Tokyo) IBISML2014-40 |
抄録 |
(和) |
(事前公開アブストラクト) Non-stationarity is an important issue for practical applications of machine learning methods. This issue particularly affects Brain-Computer Interfaces (BCI) and tends to make their use difficult. In this paper, we show a practical way to make Common Spatial Pattern (CSP), a classical feature extraction that is particularly useful in BCI, robust to non-stationarity. To do so, we did not modify the CSP method itself, but rather make the covariance estimation (used as input by every CSP variant) more robust to non-stationarity. Those robust estimators are derived using a classical importance-weighting scenario. Finally, we highlight the behaviour of our robust framework on a toy dataset and show gains of accuracy on a real-life BCI dataset. |
(英) |
Non-stationarity is an important issue for practical applications of machine learning methods. This issue particularly affects Brain-Computer Interfaces (BCI) and tends to make their use difficult. In this paper, we show a practical way to make Common Spatial Pattern (CSP), a classical feature extraction that is particularly useful in BCI, robust to non-stationarity. To do so, we did not modify the CSP method itself, but rather make the covariance estimation (used as input by every CSP variant) more robust to non-stationarity. Those robust estimators are derived using a classical importance-weighting scenario. Finally, we highlight the behaviour of our robust framework on a toy dataset and show gains of accuracy on a real-life BCI dataset. |
キーワード |
(和) |
/ / / / / / / |
(英) |
Covariance estimation / Common Spatial Pattern / Brain-Computer Interface / / / / / |
文献情報 |
信学技報, vol. 114, no. 306, IBISML2014-40, pp. 41-48, 2014年11月. |
資料番号 |
IBISML2014-40 |
発行日 |
2014-11-10 (IBISML) |
ISSN |
Print edition: ISSN 0913-5685 Online edition: ISSN 2432-6380 |
著作権に ついて |
技術研究報告に掲載された論文の著作権は電子情報通信学会に帰属します.(許諾番号:10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) |
PDFダウンロード |
IBISML2014-40 |