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IJCNN
2008
IEEE
14 years 3 months ago
Sparse support vector machines trained in the reduced empirical feature space
— We discuss sparse support vector machines (sparse SVMs) trained in the reduced empirical feature space. Namely, we select the linearly independent training data by the Cholesky...
Kazuki Iwamura, Shigeo Abe
IJCNN
2008
IEEE
14 years 3 months ago
Using Variable Neighborhood Search to improve the Support Vector Machine performance in embedded automotive applications
— In this work we show that a metaheuristic, the Variable Neighborhood Search (VNS), can be effectively used in order to improve the performance of the hardware–friendly versio...
Enrique Alba, Davide Anguita, Alessandro Ghio, San...
ICC
2007
IEEE
133views Communications» more  ICC 2007»
14 years 3 months ago
Machine Learning for Automatic Defence Against Distributed Denial of Service Attacks
— Distributed Denial of Service attacks pose a serious threat to many businesses which rely on constant availability of their network services. Companies like Google, Yahoo and A...
Stefan Seufert, Darragh O'Brien
ICANN
2007
Springer
14 years 2 months ago
Incremental and Decremental Learning for Linear Support Vector Machines
Abstract. We present a method to find the exact maximal margin hyperplane for linear Support Vector Machines when a new (existing) component is added (removed) to (from) the inner...
Enrique Romero, Ignacio Barrio, Lluís Belan...
ISNN
2007
Springer
14 years 2 months ago
A Hierarchical Self-organizing Associative Memory for Machine Learning
This paper proposes novel hierarchical self-organizing associative memory architecture for machine learning. This memory architecture is characterized with sparse and local interco...
Janusz A. Starzyk, Haibo He, Yue Li