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» Input Modeling Using Quantile Statistical Methods
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91
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IWCLS
2007
Springer
15 years 9 months ago
A Principled Foundation for LCS
In this paper we explicitly identify the probabilistic model underlying LCS by linking it to a generalisation of the common Mixture-of-Experts model. Having an explicit representa...
Jan Drugowitsch, Alwyn Barry
102
Voted
DEXAW
2007
IEEE
116views Database» more  DEXAW 2007»
15 years 9 months ago
Regression Relevance Models for Data Fusion
Data fusion has been investigated by many researchers in the information retrieval community and has become an effective technique for improving retrieval effectiveness. In this p...
Shengli Wu, Yaxin Bi, Sally I. McClean
96
Voted
INFORMATICALT
2008
91views more  INFORMATICALT 2008»
15 years 2 months ago
Lloyd-Max's Algorithm Implementation in Speech Coding Algorithm Based on Forward Adaptive Technique
In this paper a detail analysis of speech coding algorithm based on forward adaptive technique is carried out. We consider an algorithm that works on frame-by-frame basis, where a ...
Jelena Nikolic, Zoran Peric
108
Voted
ACCV
2009
Springer
15 years 9 months ago
Levels of Details for Gaussian Mixture Models
Mixtures of Gaussians are a crucial statistical modeling tool at the heart of many challenging applications in computer vision and machine learning. In this paper, we first descri...
Vincent Garcia, Frank Nielsen, Richard Nock
142
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JMLR
2010
129views more  JMLR 2010»
14 years 9 months ago
Expectation Truncation and the Benefits of Preselection In Training Generative Models
We show how a preselection of hidden variables can be used to efficiently train generative models with binary hidden variables. The approach is based on Expectation Maximization (...
Jörg Lücke, Julian Eggert