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» An Algorithm for Learning Abductive Rules
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NIPS
2000
13 years 9 months ago
An Information Maximization Approach to Overcomplete and Recurrent Representations
The principle of maximizing mutual information is applied to learning overcomplete and recurrent representations. The underlying model consists of a network of input units driving...
Oren Shriki, Haim Sompolinsky, Daniel D. Lee
PKDD
2010
Springer
152views Data Mining» more  PKDD 2010»
13 years 6 months ago
Online Knowledge-Based Support Vector Machines
Prior knowledge, in the form of simple advice rules, can greatly speed up convergence in learning algorithms. Online learning methods predict the label of the current point and the...
Gautam Kunapuli, Kristin P. Bennett, Amina Shabbee...
ICC
2007
IEEE
102views Communications» more  ICC 2007»
14 years 2 months ago
Use of Fuzzy Bayesian Clustering to Enhance Generalization Capacity of Radio Network Planning Tool
— To enhance the generalization capacity of a distribution learning method, we propose to use a fuzzy Bayesian framework based on Bayes rules. The precision of the learning resul...
Zakaria Nouir, Berna Sayraç, Benoît F...
APWEB
2005
Springer
14 years 1 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,...
IJCNN
2000
IEEE
13 years 11 months ago
Unsupervised Classification of Complex Clusters in Networks of Spiking Neurons
For unsupervised clustering in a network of spiking neurons we develop a temporal encoding of continuously valued data to obtain arbitrary clustering capacity and precision with a...
Sander M. Bohte, Johannes A. La Poutré, Joo...