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ICML
2008
IEEE
15 years 10 months ago
An HDP-HMM for systems with state persistence
The hierarchical Dirichlet process hidden Markov model (HDP-HMM) is a flexible, nonparametric model which allows state spaces of unknown size to be learned from data. We demonstra...
Emily B. Fox, Erik B. Sudderth, Michael I. Jordan,...
PAKDD
2007
ACM
152views Data Mining» more  PAKDD 2007»
15 years 3 months ago
Spectral Clustering Based Null Space Linear Discriminant Analysis (SNLDA)
While null space based linear discriminant analysis (NLDA) obtains a good discriminant performance, the ability easily suffers from an implicit assumption of Gaussian model with sa...
Wenxin Yang, Junping Zhang
KDD
2010
ACM
233views Data Mining» more  KDD 2010»
15 years 1 months ago
Evolutionary hierarchical dirichlet processes for multiple correlated time-varying corpora
Mining cluster evolution from multiple correlated time-varying text corpora is important in exploratory text analytics. In this paper, we propose an approach called evolutionary h...
Jianwen Zhang, Yangqiu Song, Changshui Zhang, Shix...
CSDA
2007
151views more  CSDA 2007»
14 years 9 months ago
Robust semiparametric mixing for detecting differentially expressed genes in microarray experiments
An important goal of microarray studies is the detection of genes that show significant changes in observed expressions when two or more classes of biological samples such as tre...
Marco Alfò, Alessio Farcomeni, Luca Tardell...
BMCBI
2010
113views more  BMCBI 2010»
14 years 9 months ago
Probabilistic Principal Component Analysis for Metabolomic Data
Background: Data from metabolomic studies are typically complex and high-dimensional. Principal component analysis (PCA) is currently the most widely used statistical technique fo...
Gift Nyamundanda, Lorraine Brennan, Isobel Claire ...