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» Hierarchical mixture models: a probabilistic analysis
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NIPS
2001
13 years 6 months ago
Latent Dirichlet Allocation
We describe latent Dirichlet allocation (LDA), a generative probabilistic model for collections of discrete data such as text corpora. LDA is a three-level hierarchical Bayesian m...
David M. Blei, Andrew Y. Ng, Michael I. Jordan
GFKL
2004
Springer
107views Data Mining» more  GFKL 2004»
13 years 10 months ago
Hierarchical Mixture Models for Nested Data Structures
A hierarchical extension of the finite mixture model is presented that can be used for the analysis of nested data structures. The model permits a simultaneous model-based cluster...
Jeroen K. Vermunt, Jay Magidson
ICASSP
2011
IEEE
12 years 9 months ago
Improving melody extraction using Probabilistic Latent Component Analysis
We propose a new approach for automatic melody extraction from polyphonic audio, based on Probabilistic Latent Component Analysis (PLCA). An audio signal is first divided into vo...
Jinyu Han, Ching-Wei Chen
BMCBI
2007
138views more  BMCBI 2007»
13 years 5 months ago
A full Bayesian hierarchical mixture model for the variance of gene differential expression
Background: In many laboratory-based high throughput microarray experiments, there are very few replicates of gene expression levels. Thus, estimates of gene variances are inaccur...
Samuel O. M. Manda, Rebecca E. Walls, Mark S. Gilt...
KDD
2006
ACM
175views Data Mining» more  KDD 2006»
14 years 5 months ago
A mixture model for contextual text mining
Contextual text mining is concerned with extracting topical themes from a text collection with context information (e.g., time and location) and comparing/analyzing the variations...
Qiaozhu Mei, ChengXiang Zhai