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» Bayesian Maximum Margin Principal Component Analysis
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ICUMT
2009
13 years 4 months ago
A Bayesian analysis of Compressive Sensing data recovery in Wireless Sensor Networks
Abstract--In this paper we address the task of accurately reconstructing a distributed signal through the collection of a small number of samples at a data gathering point using Co...
Riccardo Masiero, Giorgio Quer, Michele Rossi, Mic...
CSDA
2011
13 years 1 months ago
Mapping electron density in the ionosphere: A principal component MCMC algorithm
The outer layers of the Earth’s atmosphere are known as the ionosphere, a plasma of free electrons and positively charged atomic ions. The electron density of the ionosphere var...
Eman Khorsheed, Merrilee Hurn, Christopher Jenniso...
NIPS
1998
13 years 7 months ago
Probabilistic Image Sensor Fusion
We present a probabilistic method for fusion of images produced by multiple sensors. The approach is based on an image formation model in which the sensor images are noisy, locall...
Ravi K. Sharma, Todd K. Leen, Misha Pavel
NIPS
2000
13 years 7 months ago
Automatic Choice of Dimensionality for PCA
A central issue in principal component analysis (PCA) is choosing the number of principal components to be retained. By interpreting PCA as density estimation, this paper shows ho...
Thomas P. Minka
ICA
2007
Springer
13 years 8 months ago
Bayesian Estimation of Overcomplete Independent Feature Subspaces for Natural Images
In this paper, we propose a Bayesian estimation approach to extend independent subspace analysis (ISA) for an overcomplete representation without imposing the orthogonal constraint...
Libo Ma, Liqing Zhang