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Relevance vector machine

Known as: RVM 
In mathematics, a Relevance Vector Machine (RVM) is a machine learning technique that uses Bayesian inference to obtain parsimonious solutions for… 
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Papers overview

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2015
2015
Many machine learning and signal processing tasks involve computing sparse representations using an overcomplete set of features… 
2013
2013
In this work we propose a heteroscedastic generalization to RVM, a fast Bayesian framework for regression, based on some recent… 
2012
2012
To solve the fault prognostic problem caused by small samples,a model based on grey relevance vector machine(RVM) is presented.At… 
2011
2011
The entire thesis text is included in the research.pf file; the official abstract appears in the short.pdf file; a non-technical… 
2010
2010
To solve a kind of fault prognostic problem,an algorithm based on relevance vector machine(RVM) regression is presented.The… 
2010
2010
We adopt the Relevance Vector Machine (RVM) framework to handle cases of tablestructured data such as image blocks and image… 
2010
2010
Problem statement: In computer vision and robotics, one of the typica l tasks is to identify specific objects in an image and to… 
2008
2008
The aim of this report is to detail the implementation of a sparse Bayesian Mixture of Experts (ME) [2] for solving a one-to-many… 
2006
2006
This paper presents a fast algorithm for training relevance vector machine classifiers for dealing with large data set. The core… 
2005
2005
The task of visual object recognition benefits from feature selection as it reduces the amount of computation in recognizing a…