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» Modeling the Variability Space of Self-Adaptive Applications
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SPLC
2008
13 years 5 months ago
Modeling the Variability Space of Self-Adaptive Applications
Modeling self-adaptive applications is a difficult task due to the complex relationships they have with their environments. Designers of such applications strive to model accurate...
Gilles Perrouin, Franck Chauvel, Julien DeAntoni, ...
SASO
2008
IEEE
13 years 10 months ago
A Self-Adaptable Network Topology for Ambient Intelligence
Ambient Intelligence scenarios can be deployed even when the environment lacks of a underlying network infrastructure. This can be done using distributed ad-hoc networks. Ambient ...
Boris Mejías, Alfredo Cádiz, Peter V...
SDM
2008
SIAM
206views Data Mining» more  SDM 2008»
13 years 5 months ago
Latent Variable Mining with Its Applications to Anomalous Behavior Detection
In this paper, we propose a new approach to anomaly detection by looking at the latent variable space to make the first step toward latent anomaly detection. Most conventional app...
Shunsuke Hirose, Kenji Yamanishi
MLMI
2007
Springer
13 years 9 months ago
Gaussian Process Latent Variable Models for Human Pose Estimation
We describe a method for recovering 3D human body pose from silhouettes. Our model is based on learning a latent space using the Gaussian Process Latent Variable Model (GP-LVM) [1]...
Carl Henrik Ek, Philip H. S. Torr, Neil D. Lawrenc...
ICDM
2006
IEEE
158views Data Mining» more  ICDM 2006»
13 years 9 months ago
A Probability Distribution Of Functional Random Variable With A Functional Data Analysis Application
Probability distributions are central tools for probabilistic modeling in data mining, and they lack in functional data analysis (FDA). In this paper we propose a probability dist...
Etienne Cuvelier, Monique Noirhomme-Fraiture