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» Online Learning for Matrix Factorization and Sparse Coding
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JMLR
2010
129views more  JMLR 2010»
13 years 13 days 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
ISCAS
2006
IEEE
96views Hardware» more  ISCAS 2006»
13 years 11 months ago
On the initialization of the DNMF algorithm
— A subspace supervised learning algorithm named Discriminant Non-negative Matrix Factorization (DNMF) has been recently proposed for classifying human facial expressions. It dec...
Ioan Buciu, Nikos Nikolaidis, Ioannis Pitas
APWEB
2005
Springer
13 years 11 months ago
Mining Quantitative Associations in Large Database
Association Rule Mining algorithms operate on a data matrix to derive association rule, discarding the quantities of the items, which contains valuable information. In order to mak...
Chenyong Hu, Yongji Wang, Benyu Zhang, Qiang Yang,...
CRIWG
2004
13 years 7 months ago
An Integrated Approach for Analysing and Assessing the Performance of Virtual Learning Groups
Collaborative distance learning involves a variety of elements and factors that have to be considered and measured in order to analyse and assess group and individual performance m...
Thanasis Daradoumis, Alejandra Martínez-Mon...
PERCOM
2005
ACM
14 years 5 months ago
Adaptive Temporal Radio Maps for Indoor Location Estimation
In this paper, we present a novel method to adapt the temporal radio maps for indoor location determination by offsetting the variational environmental factors using data mining t...
Jie Yin, Qiang Yang, Lionel M. Ni