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» Perceptual Learning and Abstraction in Machine Learning
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ICANN
2010
Springer
13 years 9 months ago
Empirical Analysis of the Divergence of Gibbs Sampling Based Learning Algorithms for Restricted Boltzmann Machines
Abstract. Learning algorithms relying on Gibbs sampling based stochastic approximations of the log-likelihood gradient have become a common way to train Restricted Boltzmann Machin...
Asja Fischer, Christian Igel
WWIC
2010
Springer
193views Communications» more  WWIC 2010»
14 years 17 days ago
0day Anomaly Detection Made Possible Thanks to Machine Learning
Abstract. This paper proposes new cognitive algorithms and mechanisms for detecting 0day attacks targeting the Internet and its communication performances and behavior. For this pu...
Philippe Owezarski, Johan Mazel, Yann Labit
JIIS
2000
120views more  JIIS 2000»
13 years 8 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...
IJON
2006
161views more  IJON 2006»
13 years 8 months ago
Evolving hybrid ensembles of learning machines for better generalisation
Ensembles of learning machines have been formally and empirically shown to outperform (generalise better than) single predictors in many cases. Evidence suggests that ensembles ge...
Arjun Chandra, Xin Yao
ARTMED
1999
92views more  ARTMED 1999»
13 years 8 months ago
Two-Stage Machine Learning model for guideline development
We present a Two-Stage Machine Learning (ML) model as a data mining method to develop practice guidelines and apply it to the problem of dementia staging. Dementia staging in clin...
Subramani Mani, William Rodman Shankle, Malcolm B....