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» Analysis techniques for microarray time-series data
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ICDM
2006
IEEE
193views Data Mining» more  ICDM 2006»
14 years 2 months ago
Feature Subset Selection on Multivariate Time Series with Extremely Large Spatial Features
Several spatio-temporal data collected in many applications, such as fMRI data in medical applications, can be represented as a Multivariate Time Series (MTS) matrix with m rows (...
Hyunjin Yoon, Cyrus Shahabi

Publication
273views
13 years 3 months ago
 3D Visualization of Multiple Time Series on Maps
Abstract—In the analysis of spatially-referenced timedependent data, gaining an understanding of the spatiotemporal distributions and relationships among the attributes in the...
Sidharth Thakur, Andrew J. Hanson
IDEAL
2004
Springer
14 years 2 months ago
Combining Local and Global Models to Capture Fast and Slow Dynamics in Time Series Data
Many time series exhibit dynamics over vastly different time scales. The standard way to capture this behavior is to assume that the slow dynamics are a “trend”, to de-trend t...
Michael Small
TMI
2010
175views more  TMI 2010»
13 years 3 months ago
Spatially Adaptive Mixture Modeling for Analysis of fMRI Time Series
Within-subject analysis in fMRI essentially addresses two problems, the detection of brain regions eliciting evoked activity and the estimation of the underlying dynamics. In [1, 2...
Thomas Vincent, Laurent Risser, Philippe Ciuciu
ICANN
2001
Springer
14 years 1 months ago
Generalized Relevance LVQ for Time Series
Abstract. An application of the recently proposed generalized relevance learning vector quantization (GRLVQ) to the analysis and modeling of time series data is presented. We use G...
Marc Strickert, Thorsten Bojer, Barbara Hammer