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ISNN
2004
Springer
16 years 4 days ago
Fuzzy-Kernel Learning Vector Quantization
This paper presents an unsupervised fuzzy-kernel learning vector quantization algorithm called FKLVQ. FKLVQ is a batch type of clustering learning network by fusing the batch learn...
Daoqiang Zhang, Songcan Chen, Zhi-Hua Zhou
ICANN
2009
Springer
15 years 11 months ago
Constrained Learning Vector Quantization or Relaxed k-Separability
Neural networks and other sophisticated machine learning algorithms frequently miss simple solutions that can be discovered by a more constrained learning methods. Transition from ...
Marek Grochowski, Wlodzislaw Duch
ECAL
2001
Springer
15 years 11 months ago
Evolution of Reinforcement Learning in Uncertain Environments: Emergence of Risk-Aversion and Matching
Reinforcement learning (RL) is a fundamental process by which organisms learn to achieve a goal from interactions with the environment. Using Artificial Life techniques we derive ...
Yael Niv, Daphna Joel, Isaac Meilijson, Eytan Rupp...
ICANN
2001
Springer
15 years 11 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
FLAIRS
2001
15 years 8 months ago
Structural Learning in Object Oriented Domains
When constructing a Bayesian network, it can be advantageous to employ structural learning algorithms to combine knowledge captured in databases with prior information provided by...
Olav Bangsø, Helge Langseth, Thomas D. Niel...