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UAI
2003
15 years 8 months ago
Large-Sample Learning of Bayesian Networks is NP-Hard
In this paper, we provide new complexity results for algorithms that learn discrete-variable Bayesian networks from data. Our results apply whenever the learning algorithm uses a ...
David Maxwell Chickering, Christopher Meek, David ...
FUIN
2006
107views more  FUIN 2006»
15 years 6 months ago
Learning Sunspot Classification
Sunspots are the subject of interest to many astronomers and solar physicists. Sunspot observation, analysis and classification form an important part of furthering the knowledge a...
Trung Thanh Nguyen, Claire P. Willis, Derek J. Pad...
JCM
2007
105views more  JCM 2007»
15 years 6 months ago
Generalization Capabilities Enhancement of a Learning System by Fuzzy Space Clustering
Abstract— We have used measurements taken on real network to enhance the performance of our radio network planning tool. A distribution learning technique is adopted to realize t...
Zakaria Nouir, Berna Sayraç, Benoît F...
JIIS
2000
120views more  JIIS 2000»
15 years 6 months ago
Machine Learning for Intelligent Processing of Printed Documents
Abstract. A paper document processing system is an information system component which transforms information on printed or handwritten documents into a computer-revisable form. In ...
Floriana Esposito, Donato Malerba, Francesca A. Li...
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SAC
2008
ACM
15 years 6 months ago
Efficient concept clustering for ontology learning using an event life cycle on the web
Ontology learning integrates many complementary techniques, including machine learning, natural language processing, and data mining. Specifically, clustering techniques facilitat...
Sangsoo Sung, Seokkyung Chung, Dennis McLeod