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Bayesian programming

Bayesian programming is a formalism and a methodology to specify probabilistic models and solve problems when less than the necessary information is… 
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Related topics

Related topics

27 relations
Abductive logic programmingBaum–Welch algorithmBayesian networkBelief propagation

Broader (1)

Artificial intelligence

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2015
2015
NetCodec: Community Detection from Individual Activities
The real social network and associated communities are often hidden under the declared friend or group lists in social networks… 
2015
2015
Bayesian quantile regression with approximate likelihood
Quantile regression is often used when a comprehensive relationship between a response variable and one or more explanatory… 
Review
2010
Review
2010
Feature based opinion mining of online free format customer reviews using frequency distribution and Bayesian statistics
Nowadays, a large number of websites allow users to post reviews about products they bought. There are thousands of reviews of… 
2010
2010
Gender classification from unconstrained video sequences
This paper presents the first investigation into the classification of faces from unconstrained video sequences in natural scenes… 
2009
2009
Predicting Missing Items in Shopping Carts
Existing research in association mining has focused mainly on how to expedite the search for frequently co-occurring groups of… 
2008
2008
Tracking facial features under occlusions and recognizing facial expressions in sign language
This paper presents work towards recognizing facial expressions that are used in sign language recognition. Facial features are… 
2006
2006
Variational Method for Image Denoising by Distributed Genetic Algorithms on GRID Environment
The aim of this paper is to present a novel distributed genetic algorithm architecture implemented on grid computing by using the… 
2006
2006
Estimation of project success using Bayesian classifier
The software projects are considered to be successful if the cost and the duration are within the estimated ones and the quality… 
2006
2006
A prior for steepness in stock-recruitment relationships, based on an evolutionary persistence principle
Priors are existing information or beliefs that are needed in Bayesian analysis. Informative priors are important in obtaining… 
Highly Cited
1999
Highly Cited
1999
The Practice of Bayesian Analysis
The purpose of this book is twofold. First, it has been written to advertise the advantages a Bayesian analysis can bring. New… 
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