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SSPR
2004
Springer
14 years 2 months ago
An MCMC Feature Selection Technique for Characterizing and Classifying Spatial Region Data
We focus on characterizing spatial region data when distinct classes of structural patterns are present. We propose a novel statistical approach based on a supervised framework for...
Despina Kontos, Vasileios Megalooikonomou, Marc J....
ICML
2009
IEEE
14 years 9 months ago
Tractable nonparametric Bayesian inference in Poisson processes with Gaussian process intensities
The inhomogeneous Poisson process is a point process that has varying intensity across its domain (usually time or space). For nonparametric Bayesian modeling, the Gaussian proces...
Ryan Prescott Adams, Iain Murray, David J. C. MacK...
BMCBI
2007
127views more  BMCBI 2007»
13 years 9 months ago
A Latent Variable Approach for Meta-Analysis of Gene Expression Data from Multiple Microarray Experiments
Background: With the explosion in data generated using microarray technology by different investigators working on similar experiments, it is of interest to combine results across...
Hyungwon Choi, Ronglai Shen, Arul M. Chinnaiyan, D...
ICIP
2009
IEEE
14 years 9 months ago
Lidar Waveform Modeling Using A Marked Point Process
Lidar waveforms are 1D signal consisting of a train of echoes where each of them correspond to a scattering target of the Earth surface. Modeling these echoes with the appropriate...
SADM
2010
196views more  SADM 2010»
13 years 3 months ago
Bayesian adaptive nearest neighbor
: The k nearest neighbor classification (k-NN) is a very simple and popular method for classification. However, it suffers from a major drawback, it assumes constant local class po...
Ruixin Guo, Sounak Chakraborty