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» A multi-objective approach to RBF network learning
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IJON
2002
103views more  IJON 2002»
13 years 5 months ago
RBF networks training using a dual extended Kalman filter
: A new supervised learning procedure for training RBF networks is proposed. It uses a pair of parallel running Kalman filters to sequentially update both the output weights and th...
Iulian B. Ciocoiu
ISNN
2007
Springer
13 years 11 months ago
Neural-Based Separating Method for Nonlinear Mixtures
A neural-based method for source separation in nonlinear mixture is proposed in this paper. A cost function, which consists of the mutual information and partial moments of the out...
Ying Tan
IEEECIT
2010
IEEE
13 years 3 months ago
Learning Autonomic Security Reconfiguration Policies
Abstract--We explore the idea of applying machine learning techniques to automatically infer risk-adaptive policies to reconfigure a network security architecture when the context ...
Juan E. Tapiador, John A. Clark
TEC
2010
191views more  TEC 2010»
13 years 1 days ago
Particle Swarm Optimization Aided Orthogonal Forward Regression for Unified Data Modeling
We propose a unified data modeling approach that is equally applicable to supervised regression and classification applications, as well as to unsupervised probability density func...
Sheng Chen, Xia Hong, Chris J. Harris
ICANN
2001
Springer
13 years 9 months ago
Incremental Support Vector Machine Learning: A Local Approach
Abstract. In this paper, we propose and study a new on-line algorithm for learning a SVM based on Radial Basis Function Kernel: Local Incremental Learning of SVM or LISVM. Our meth...
Liva Ralaivola, Florence d'Alché-Buc