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» A Hierarchical Latent Variable Model for Data Visualization
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JMLR
2006
138views more  JMLR 2006»
15 years 6 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»
15 years 6 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
15 years 4 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»
16 years 1 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
15 years 8 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...