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» Robust Induction of Process Models from Time-Series Data
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DMIN
2008
241views Data Mining» more  DMIN 2008»
13 years 8 months ago
Leakage Detection by Adaptive Process Modeling
Abstract-- In this paper, we propose an adaptive linear approach for time series modeling and steam line leakage detection. Weighted recursive least squares (WRLS) method is used f...
Jaakko Talonen, Miki Sirola, Jukka Parviainen
PKDD
2010
Springer
184views Data Mining» more  PKDD 2010»
13 years 5 months ago
Shift-Invariant Grouped Multi-task Learning for Gaussian Processes
Multi-task learning leverages shared information among data sets to improve the learning performance of individual tasks. The paper applies this framework for data where each task ...
Yuyang Wang, Roni Khardon, Pavlos Protopapas
TIT
2008
119views more  TIT 2008»
13 years 7 months ago
Asymptotic Properties of the Detrended Fluctuation Analysis of Long-Range-Dependent Processes
In the past few years, a certain number of authors have proposed analysis methods of the time series built from a long range dependence noise. One of these methods is the Detrended...
Jean-Marc Bardet, Imen Kammoun
ECML
2006
Springer
13 years 11 months ago
Learning Process Models with Missing Data
Abstract. In this paper, we review the task of inductive process modeling, which uses domain knowledge to compose explanatory models of continuous dynamic systems. Next we discuss ...
Will Bridewell, Pat Langley, Steve Racunas, Stuart...
ICASSP
2011
IEEE
12 years 11 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...