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» Recursive Algorithms of Time Series Observations Recognition
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ICML
2008
IEEE
15 years 10 months ago
Modeling interleaved hidden processes
Hidden Markov models assume that observations in time series data stem from some hidden process that can be compactly represented as a Markov chain. We generalize this model by as...
Niels Landwehr
KDD
2005
ACM
160views Data Mining» more  KDD 2005»
15 years 10 months ago
Optimizing time series discretization for knowledge discovery
Knowledge Discovery in time series usually requires symbolic time series. Many discretization methods that convert numeric time series to symbolic time series ignore the temporal ...
Alfred Ultsch, Fabian Mörchen
ARTMED
2002
92views more  ARTMED 2002»
14 years 9 months ago
Predicting glaucomatous visual field deterioration through short multivariate time series modelling
In bio-medical domains there are many applications involving the modelling of multivariate time series (MTS) data. One area that has been largely overlooked so far is the particul...
Stephen Swift, Xiaohui Liu
EDBT
2010
ACM
184views Database» more  EDBT 2010»
15 years 4 months ago
Aggregation of asynchronous electric power consumption time series knowing the integral
More and more data mining algorithms are applied to a large number of long time series issued by many distributed sensors. The consequence of the huge volume of data is that data ...
Raja Chiky, Laurent Decreusefond, Georges Hé...
ICCV
2007
IEEE
15 years 11 months ago
DynamicBoost: Boosting Time Series Generated by Dynamical Systems
Boosting is a remarkably simple and flexible classification algorithm with widespread applications in computer vision. However, the application of boosting to nonEuclidean, infini...
René Vidal, Paolo Favaro