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CVPR
2008
IEEE
14 years 9 months ago
Incremental learning of nonparametric Bayesian mixture models
Clustering is a fundamental task in many vision applications. To date, most clustering algorithms work in a batch setting and training examples must be gathered in a large group b...
Ryan Gomes, Max Welling, Pietro Perona
RSS
2007
159views Robotics» more  RSS 2007»
13 years 8 months ago
Gaussian Beam Processes: A Nonparametric Bayesian Measurement Model for Range Finders
— In probabilistic mobile robotics, the development of measurement models plays a crucial role as it directly influences the efficiency and the robustness of the robot’s perf...
Christian Plagemann, Kristian Kersting, Patrick Pf...
ICANN
2009
Springer
13 years 11 months ago
Bayesian Estimation of Kernel Bandwidth for Nonparametric Modelling
Kernel density estimation (KDE) has been used in many computational intelligence and computer vision applications. In this paper we propose a Bayesian estimation method for findin...
Adrian G. Bors, Nikolaos Nasios
ICDM
2010
IEEE
147views Data Mining» more  ICDM 2010»
13 years 5 months ago
Subgroup Discovery Meets Bayesian Networks -- An Exceptional Model Mining Approach
Whenever a dataset has multiple discrete target variables, we want our algorithms to consider not only the variables themselves, but also the interdependencies between them. We pro...
Wouter Duivesteijn, Arno J. Knobbe, Ad Feelders, M...
CSB
2002
IEEE
169views Bioinformatics» more  CSB 2002»
14 years 2 days ago
Bayesian Network and Nonparametric Heteroscedastic Regression for Nonlinear Modeling of Genetic Network
We propose a new statistical method for constructing a genetic network from microarray gene expression data by using a Bayesian network. An essential point of Bayesian network con...
Seiya Imoto, SunYong Kim, Takao Goto, Sachiyo Abur...