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IJON
2011
158views more  IJON 2011»
13 years 2 months ago
Maximal Discrepancy for Support Vector Machines
Several theoretical methods have been developed in the past years to evaluate the generalization ability of a classifier: they provide extremely useful insights on the learning ph...
Davide Anguita, Alessandro Ghio, Sandro Ridella
IJON
2011
91views more  IJON 2011»
13 years 2 months ago
Asymptotic properties of mixture-of-experts models
The statistical properties of the likelihood ratio test statistic (LRTS) for mixture-of-expert models are addressed in this paper. This question is essential when estimating the nu...
Madalina Olteanu, Joseph Rynkiewicz
IJON
2011
169views more  IJON 2011»
13 years 2 months ago
Exploiting local structure in Boltzmann machines
Restricted Boltzmann Machines (RBM) are well-studied generative models. For image data, however, standard RBMs are suboptimal, since they do not exploit the local nature of image ...
Hannes Schulz, Andreas Müller 0004, Sven Behn...
IJON
2011
133views more  IJON 2011»
13 years 2 months ago
Relational generative topographic mapping
Abstract. The generative topographic mapping (GTM) has been proposed as a statistical model to represent high dimensional data by means of a sparse lattice of points in latent spac...
Andrej Gisbrecht, Bassam Mokbel, Barbara Hammer
IJON
2011
90views more  IJON 2011»
12 years 11 months ago
Fault tolerant machine learning for nanoscale cognitive radio
We introduce a machine learning based classifier that identifies free radio channels for cognitive radio. The architecture is designed for nanoscale implementation, under nanosc...
Joni Pajarinen, Jaakko Peltonen, Mikko A. Uusitalo