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FSKD
2005
Springer
267views Fuzzy Logic» more  FSKD 2005»
14 years 29 days ago
Preventing Meaningless Stock Time Series Pattern Discovery by Changing Perceptually Important Point Detection
Discovery of interesting or frequently appearing time series patterns is one of the important tasks in various time series data mining applications. However, recent research critic...
Tak-Chung Fu, Fu-Lai Chung, Robert W. P. Luk, Chak...
ICML
2007
IEEE
14 years 8 months ago
Modeling changing dependency structure in multivariate time series
We show how to apply the efficient Bayesian changepoint detection techniques of Fearnhead in the multivariate setting. We model the joint density of vector-valued observations usi...
Xiang Xuan, Kevin P. Murphy
TMI
2008
136views more  TMI 2008»
13 years 7 months ago
Classification of fMRI Time Series in a Low-Dimensional Subspace With a Spatial Prior
We propose a new method for detecting activation in functional magnetic resonance imaging (fMRI) data. We project the fMRI time series on a low-dimensional subspace spanned by wave...
François G. Meyer, Xilin Shen
VIS
2009
IEEE
163views Visualization» more  VIS 2009»
14 years 8 months ago
Visual Exploration of Climate Variability Changes Using Wavelet Analysis
Due to its nonlinear nature, the climate system shows quite high natural variability on different time scales, including multiyear oscillations such as the El Ni~no Southern Oscill...
Heike Jänicke, Michael Böttinger, Uwe Mikolaje...
ADMA
2006
Springer
112views Data Mining» more  ADMA 2006»
14 years 1 months ago
Finding Time Series Discords Based on Haar Transform
The problem of finding anomaly has received much attention recently. However, most of the anomaly detection algorithms depend on an explicit definition of anomaly, which may be i...
Ada Wai-Chee Fu, Oscar Tat-Wing Leung, Eamonn J. K...