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ECML
2004
Springer
16 years 5 days ago
Applying Support Vector Machines to Imbalanced Datasets
Support Vector Machines (SVM) have been extensively studied and have shown remarkable success in many applications. However the success of SVM is very limited when it is applied to...
Rehan Akbani, Stephen Kwek, Nathalie Japkowicz
JCDL
2003
ACM
160views Education» more  JCDL 2003»
16 years 1 days ago
Automatic Document Metadata Extraction Using Support Vector Machines
Automatic metadata generation provides scalability and usability for digital libraries and their collections. Machine learning methods offer robust and adaptable automatic metadat...
Hui Han, C. Lee Giles, Eren Manavoglu, Hongyuan Zh...
ICML
2010
IEEE
15 years 7 months ago
Restricted Boltzmann Machines are Hard to Approximately Evaluate or Simulate
Restricted Boltzmann Machines (RBMs) are a type of probability model over the Boolean cube {-1, 1}n that have recently received much attention. We establish the intractability of ...
Philip M. Long, Rocco A. Servedio
AIS
2000
Springer
15 years 6 months ago
Early-connectionism machines
: In this paper I put forward a reconstruction of the evolution of certain explanatory hypotheses on the neural basis of association and learning that are the premises of connectio...
Roberto Cordeschi
ML
2002
ACM
220views Machine Learning» more  ML 2002»
15 years 6 months ago
Bayesian Methods for Support Vector Machines: Evidence and Predictive Class Probabilities
I describe a framework for interpreting Support Vector Machines (SVMs) as maximum a posteriori (MAP) solutions to inference problems with Gaussian Process priors. This probabilisti...
Peter Sollich