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» On-line support vector machines and optimization strategies
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ICDM
2006
IEEE
119views Data Mining» more  ICDM 2006»
15 years 3 months ago
Fast On-line Kernel Learning for Trees
Kernel methods have been shown to be very effective for applications requiring the modeling of structured objects. However kernels for structures usually are too computational dem...
Fabio Aiolli, Giovanni Da San Martino, Alessandro ...
IDEAL
2004
Springer
15 years 2 months ago
Kernel Density Construction Using Orthogonal Forward Regression
Abstract— The paper presents an efficient construction algorithm for obtaining sparse kernel density estimates based on a regression approach that directly optimizes model gener...
Sheng Chen, Xia Hong, Chris J. Harris
HAIS
2009
Springer
15 years 2 months ago
Pareto-Based Multi-output Model Type Selection
In engineering design the use of approximation models (= surrogate models) has become standard practice for design space exploration, sensitivity analysis, visualization and optimi...
Dirk Gorissen, Ivo Couckuyt, Karel Crombecq, Tom D...
NECO
2007
115views more  NECO 2007»
14 years 9 months ago
Training Recurrent Networks by Evolino
In recent years, gradient-based LSTM recurrent neural networks (RNNs) solved many previously RNN-unlearnable tasks. Sometimes, however, gradient information is of little use for t...
Jürgen Schmidhuber, Daan Wierstra, Matteo Gag...
TNN
2010
185views Management» more  TNN 2010»
14 years 4 months ago
An adaptive multiobjective approach to evolving ART architectures
In this paper, we present the evolution of adaptive resonance theory (ART) neural network architectures (classifiers) using a multiobjective optimization approach. In particular, w...
Assem Kaylani, Michael Georgiopoulos, Mansooreh Mo...