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» Learning of Boolean Functions Using Support Vector Machines
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ML
2008
ACM
115views Machine Learning» more  ML 2008»
13 years 9 months ago
Calling variadic functions from a strongly-typed language
The importance of providing a mechanism to call C functions from high-level languages has been understood for many years and, these days, almost all statically-typed high-level-la...
Matthias Blume, Mike Rainey, John H. Reppy
TEC
2008
135views more  TEC 2008»
13 years 8 months ago
Evolving Output Codes for Multiclass Problems
In this paper, we propose an evolutionary approach to the design of output codes for multiclass pattern recognition problems. This approach has the advantage of taking into account...
Nicolás García-Pedrajas, Colin Fyfe
ESANN
2006
13 years 10 months ago
LS-SVM functional network for time series prediction
Usually time series prediction is done with regularly sampled data. In practice, however, the data available may be irregularly sampled. In this case the conventional prediction me...
Tuomas Kärnä, Fabrice Rossi, Amaury Lend...
ECTEL
2009
Springer
14 years 1 months ago
The Conceptual and Architectural Design of a System Supporting Exploratory Learning of Mathematics Generalisation
Abstract. The MiGen project is designing and developing an intelligent, exploratory environment to support 11–14-year-old students in their learning of mathematical generalisatio...
Darren Pearce, Alexandra Poulovassilis
BMCBI
2004
140views more  BMCBI 2004»
13 years 9 months ago
What can we learn from noncoding regions of similarity between genomes?
Background: In addition to known protein-coding genes, large amounts of apparently non-coding sequence are conserved between the human and mouse genomes. It seems reasonable to as...
Thomas A. Down, Tim J. P. Hubbard