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» Making inferences with small numbers of training sets
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PRL
2007
154views more  PRL 2007»
13 years 8 months ago
Regularized mixture discriminant analysis
Abstract – In this paper we seek a Gaussian mixture model (GMM) of the classconditional densities for plug-in Bayes classification. We propose a method for setting the number of ...
Zohar Halbe, Mayer Aladjem
ICGI
2004
Springer
14 years 2 months ago
Identifying Clusters from Positive Data
The present work studies clustering from an abstract point of view and investigates its properties in the framework of inductive inference. Any class S considered is given by a hyp...
John Case, Sanjay Jain, Eric Martin, Arun Sharma, ...
CHI
2007
ACM
14 years 9 months ago
Tactile feedback for mobile interactions
We present a study investigating the use of vibrotactile feedback for touch-screen keyboards on PDAs. Such keyboards are hard to use when mobile as keys are very small. We conduct...
Stephen A. Brewster, Faraz Chohan, Lorna M. Brown
IJCNN
2000
IEEE
14 years 1 months ago
Analog Hardware Implementation of the Random Neural Network Model
This paper presents a simple continuous analog hardware realization of the Random Neural Network (RNN) model. The proposed circuit uses the general principles resulting from the u...
Hossam Abdelbaki, Erol Gelenbe, Said E. El-Khamy
UAI
2003
13 years 10 months ago
Exploiting Locality in Searching the Web
Published experiments on spidering the Web suggest that, given training data in the form of a (relatively small) subgraph of the Web containing a subset of a selected class of tar...
Joel Young, Thomas Dean