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WSC
1998
13 years 8 months ago
Integrating Neural Networks with Special Purpose Simulation
Traditional methods of dealing with variability in simulation input data are mainly stochastic. This is most often the best method to use if the factors affecting the variation or...
Dany Hajjar, Simaan M. AbouRizk, Kevin Mather
BMCBI
2011
13 years 2 months ago
NClassG+: A classifier for non-classically secreted Gram-positive bacterial proteins
Background: Most predictive methods currently available for the identification of protein secretion mechanisms have focused on classically secreted proteins. In fact, only two met...
Daniel Restrepo-Montoya, Camilo Pino, Luis F. Ni&n...
TCSV
2002
132views more  TCSV 2002»
13 years 7 months ago
A study of real-time packet video quality using random neural networks
An important and unsolved problem today is the automatic quantification of the quality of video flows transmitted over packet networks. In particular, the ability to perform this ...
Samir Mohamed, Gerardo Rubino
NIPS
2001
13 years 8 months ago
(Not) Bounding the True Error
We present a new approach to bounding the true error rate of a continuous valued classifier based upon PAC-Bayes bounds. The method first constructs a distribution over classifier...
John Langford, Rich Caruana
ESANN
2003
13 years 8 months ago
Locally Linear Embedding versus Isotop
Abstract. Recently, a new method intended to realize conformal mappings has been published. Called Locally Linear Embedding (LLE), this method can map high-dimensional data lying o...
John Aldo Lee, Cédric Archambeau, Michel Ve...