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» Robust Bayesian Mixture Modelling
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SDM
2008
SIAM
256views Data Mining» more  SDM 2008»
15 years 3 months ago
Graph Mining with Variational Dirichlet Process Mixture Models
Graph data such as chemical compounds and XML documents are getting more common in many application domains. A main difficulty of graph data processing lies in the intrinsic high ...
Koji Tsuda, Kenichi Kurihara
109
Voted
AAAI
2010
15 years 3 months ago
A Bayesian Nonparametric Approach to Modeling Mobility Patterns
Constructing models of mobile agents can be difficult without domain-specific knowledge. Parametric models flexible enough to capture all mobility patterns that an expert believes...
Joshua Mason Joseph, Finale Doshi-Velez, Nicholas ...
FGCN
2008
IEEE
155views Communications» more  FGCN 2008»
15 years 4 months ago
Modeling the Marginal Distribution of Gene Expression with Mixture Models
We report the results of fitting mixture models to the distribution of expression values for individual genes over a broad range of normal tissues, which we call the marginal expr...
Edward Wijaya, Hajime Harada, Paul Horton
CLASSIFICATION
2006
108views more  CLASSIFICATION 2006»
15 years 2 months ago
The Practice of Cluster Analysis
Abstracts "Mixtures at the Interface" David Scott, Rice University Mixture modeling provides an effective framework for complex, high-dimensional data. The potential of m...
Jon R. Kettenring
JMLR
2012
13 years 4 months ago
Markov Logic Mixtures of Gaussian Processes: Towards Machines Reading Regression Data
We propose a novel mixtures of Gaussian processes model in which the gating function is interconnected with a probabilistic logical model, in our case Markov logic networks. In th...
Martin Schiegg, Marion Neumann, Kristian Kersting