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» Bayesian Approaches to Gaussian Mixture Modeling
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KDD
2002
ACM
155views Data Mining» more  KDD 2002»
14 years 9 months ago
SyMP: an efficient clustering approach to identify clusters of arbitrary shapes in large data sets
We propose a new clustering algorithm, called SyMP, which is based on synchronization of pulse-coupled oscillators. SyMP represents each data point by an Integrate-and-Fire oscill...
Hichem Frigui
IVC
2006
183views more  IVC 2006»
13 years 9 months ago
Augmented tracking with incomplete observation and probabilistic reasoning
An on-line algorithm for multi-object tracking is presented for monitoring a real-world scene from a single fixed camera. Potential objects are detected with adaptive backgrounds ...
Ming Xu, Tim Ellis
BMCBI
2007
194views more  BMCBI 2007»
13 years 9 months ago
Kernel-imbedded Gaussian processes for disease classification using microarray gene expression data
Background: Designing appropriate machine learning methods for identifying genes that have a significant discriminating power for disease outcomes has become more and more importa...
Xin Zhao, Leo Wang-Kit Cheung
APVIS
2010
13 years 10 months ago
Volume exploration using ellipsoidal Gaussian transfer functions
This paper presents an interactive transfer function design tool based on ellipsoidal Gaussian transfer functions (ETFs). Our approach explores volumetric features in the statisti...
Yunhai Wang, Wei Chen, Guihua Shan, Tingxin Dong, ...
CDC
2008
IEEE
14 years 3 months ago
Shannon meets Bellman: Feature based Markovian models for detection and optimization
— The goal of this paper is to develop modeling techniques for complex systems for the purposes of control, estimation, and inference: (i) A new class of Hidden Markov Models is ...
Sean P. Meyn, George Mathew