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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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Related topics

Related topics

5 relations
Gaussian processMachine learningSequential minimal optimizationSoftware patents under United States patent law

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2016
Highly Cited
2016
Estimation of Surface Soil Moisture in Irrigated Lands by Assimilation of Landsat Vegetation Indices, Surface Energy Balance Products, and Relevance Vector Machines
Spatial surface soil moisture can be an important indicator of crop conditions on farmland, but its continuous estimation remains… 
2016
2016
Relevance Vector Machine Based EEG Emotion Recognition
Personal emotions accompany us in our daily life, affecting our learning and work, therefore it is necessary to obtain better… 
2016
2016
Robust Reinforcement Learning with Relevance Vector Machines
Function approximation methods, such as neural networks, radial basis functions, and support vector machines, have been used in… 
2015
2015
Relevance vector machine for depression prediction
The objective and automated monitoring of depression using behavioral signals is confounded by the wide clinical profile of this… 
2012
2012
Recognition of human activities using a multiclass relevance vector machine
Abstract. We address the issue of human activity recognition by introducing the multiclass relevance vector machine (mRVM), the… 
2010
2010
Research on Sparse Bayesian Model and the Relevance Vector Machine
The support vector machine is successfully applied in many fields of pattern recognition,but there ere several limitations… 
2008
2008
Incremental Relevance Vector Machine with Kernel Learning
Recently, sparse kernel methods such as the Relevance Vector Machine (RVM) have become very popular for solving regression… 
2006
2006
Scaling Text Classification with Relevance Vector Machines
Text classification (TC) is a complex ubiquitous task that handles a huge amount of data. Current research has recently proved… 
2005
2005
Selecting Shape Features Using Multi-class Relevance Vector Machine
The task of visual object recognition benefits from feature selection as it reduces the amount of computation in recognizing a… 
2004
2004
Relevance vector machine analysis of functional neuroimages
We propose the use of the relevance vector machine (RVM) regression framework for statistical analysis of PET or fMRI data sets… 
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