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IJCAI
2003
15 years 8 months ago
When Discriminative Learning of Bayesian Network Parameters Is Easy
Bayesian network models are widely used for discriminative prediction tasks such as classification. Usually their parameters are determined using 'unsupervised' methods ...
Hannes Wettig, Peter Grünwald, Teemu Roos, Pe...
CORR
2010
Springer
130views Education» more  CORR 2010»
15 years 6 months ago
Approximated Structured Prediction for Learning Large Scale Graphical Models
In this paper we propose an approximated structured prediction framework for large scale graphical models and derive message-passing algorithms for learning their parameters effic...
Tamir Hazan, Raquel Urtasun
CORR
2010
Springer
258views Education» more  CORR 2010»
15 years 6 months ago
Single Frame Image super Resolution using Learned Directionlets
In this paper, a new directionally adaptive, learning based, single image super resolution method using multiple direction wavelet transform, called Directionlets is presented. Th...
A. P. Reji, Tessamma Thomas
IANDC
2006
101views more  IANDC 2006»
15 years 6 months ago
Mind change efficient learning
This paper studies efficient learning with respect to mind changes. Our starting point is the idea that a learner that is efficient with respect to mind changes minimizes mind cha...
Wei Luo, Oliver Schulte
NN
2006
Springer
153views Neural Networks» more  NN 2006»
15 years 6 months ago
An incremental network for on-line unsupervised classification and topology learning
This paper presents an on-line unsupervised learning mechanism for unlabeled data that are polluted by noise. Using a similarity thresholdbased and a local error-based insertion c...
Shen Furao, Osamu Hasegawa