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» A Hierarchical Latent Variable Model for Data Visualization
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JMLR
2006
138views more  JMLR 2006»
13 years 8 months ago
Noisy-OR Component Analysis and its Application to Link Analysis
We develop a new component analysis framework, the Noisy-Or Component Analyzer (NOCA), that targets high-dimensional binary data. NOCA is a probabilistic latent variable model tha...
Tomás Singliar, Milos Hauskrecht
BMCBI
2008
131views more  BMCBI 2008»
13 years 8 months ago
K-OPLS package: Kernel-based orthogonal projections to latent structures for prediction and interpretation in feature space
Background: Kernel-based classification and regression methods have been successfully applied to modelling a wide variety of biological data. The Kernel-based Orthogonal Projectio...
Max Bylesjö, Mattias Rantalainen, Jeremy K. N...
BMVC
2010
13 years 6 months ago
Image Topic Discovery with Saliency Detection
This work proposes a biologically inspired approach to integrate latent topic model with saliency detection. Firstly, a saliency detection algorithm is presented to discriminate s...
Zhidong Li, Yang Wang, Jing Chen, Jie Xu, John Lai...
PKDD
2009
Springer
155views Data Mining» more  PKDD 2009»
14 years 3 months ago
Dynamic Factor Graphs for Time Series Modeling
Abstract. This article presents a method for training Dynamic Factor Graphs (DFG) with continuous latent state variables. A DFG includes factors modeling joint probabilities betwee...
Piotr W. Mirowski, Yann LeCun
NIPS
2007
13 years 10 months ago
Distributed Inference for Latent Dirichlet Allocation
We investigate the problem of learning a widely-used latent-variable model – the Latent Dirichlet Allocation (LDA) or “topic” model – using distributed computation, where ...
David Newman, Arthur Asuncion, Padhraic Smyth, Max...