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» Learning to Transform Time Series with a Few Examples
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TIT
2008
119views more  TIT 2008»
14 years 9 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
CAEPIA
2003
Springer
15 years 2 months ago
Enhancing Consistency Based Diagnosis with Machine Learning Techniques
This paper proposes a diagnosis architecture that integrates consistency based diagnosis with induced time series classifiers, trying to combine the advantages of both methods. Co...
Carlos J. Alonso, Juan José Rodrígue...
EUROMICRO
2006
IEEE
15 years 1 months ago
A UML Profile and a Methodology for Real-Time Systems Design
Modern real-time systems are increasingly complex and pervasive. Model Driven Engineering (MDE) is the emerging approach for the design of complex systems, strongly the usage of a...
Cesare Bartolini, Antonia Bertolino, Guglielmo De ...
ESANN
2003
14 years 11 months ago
Autonomous learning algorithm for fully connected recurrent networks
In this paper fully connected RTRL neural networks are studied. In order to learn dynamical behaviours of linear-processes or to predict time series, an autonomous learning algori...
Edouard Leclercq, Fabrice Druaux, Dimitri Lefebvre
IJCV
2008
151views more  IJCV 2008»
14 years 9 months ago
Describing Visual Scenes Using Transformed Objects and Parts
We develop hierarchical, probabilistic models for objects, the parts composing them, and the visual scenes surrounding them. Our approach couples topic models originally developed...
Erik B. Sudderth, Antonio Torralba, William T. Fre...