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ICASSP
2011
IEEE
14 years 10 months ago
Modified embedding for multi-regime detection in nonstationary streaming data
Many practical data streams are typically composed of several states known as regimes. In this paper, we invoke phase space reconstruction methods from non-linear time series and ...
Evan Kriminger, José Carlos Príncipe...
AAAI
2007
15 years 8 months ago
Discovering Multivariate Motifs using Subsequence Density Estimation and Greedy Mixture Learning
The problem of locating motifs in real-valued, multivariate time series data involves the discovery of sets of recurring patterns embedded in the time series. Each set is composed...
David Minnen, Charles Lee Isbell Jr., Irfan A. Ess...
KDD
2007
ACM
202views Data Mining» more  KDD 2007»
16 years 6 months ago
Support feature machine for classification of abnormal brain activity
In this study, a novel multidimensional time series classification technique, namely support feature machine (SFM), is proposed. SFM is inspired by the optimization model of suppo...
Wanpracha Art Chaovalitwongse, Ya-Ju Fan, Rajesh C...
ALT
1998
Springer
15 years 10 months ago
Predictive Learning Models for Concept Drift
Concept drift means that the concept about which data is obtained may shift from time to time, each time after some minimum permanence. Except for this minimum permanence, the con...
John Case, Sanjay Jain, Susanne Kaufmann, Arun Sha...
CG
2007
Springer
15 years 6 months ago
Best analogs for replacing missing image data
Identifying the historical data that is the best analog with a pattern from which a forecast is sought allows time series data to be extrapolated. That technique of best analogs i...
Ning Chen, Clifford A. Reiter