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EUSFLAT
2003
121views Fuzzy Logic» more  EUSFLAT 2003»
13 years 11 months ago
An adaptive learning algorithm for a neo fuzzy neuron
In the paper, a new optimal learning algorithm for a neo-fuzzy neuron (NFN) is proposed. The algorithm is characteristic in that it provides online tuning of not only the synaptic...
Yevgeniy Bodyanskiy, Illya Kokshenev, Vitaliy Kolo...
ML
2008
ACM
13 years 10 months ago
Large margin vs. large volume in transductive learning
Abstract. We consider a large volume principle for transductive learning that prioritizes the transductive equivalence classes according to the volume they occupy in hypothesis spa...
Ran El-Yaniv, Dmitry Pechyony, Vladimir Vapnik
TIT
2008
224views more  TIT 2008»
13 years 10 months ago
Graph-Based Semi-Supervised Learning and Spectral Kernel Design
We consider a framework for semi-supervised learning using spectral decomposition-based unsupervised kernel design. We relate this approach to previously proposed semi-supervised l...
Rie Johnson, Tong Zhang
TSMC
2010
13 years 5 months ago
Cellular Learning Automata With Multiple Learning Automata in Each Cell and Its Applications
The cellular learning automaton (CLA), which is a4 combination of cellular automaton (CA) and learning automaton5 (LA), is introduced recently. This model is superior to CA because...
Hamid Beigy, Mohammad Reza Meybodi
IDA
2009
Springer
14 years 4 months ago
Canonical Dual Approach to Binary Factor Analysis
Abstract. Binary Factor Analysis (BFA) is a typical problem of Independent Component Analysis (ICA) where the signal sources are binary. Parameter learning and model selection in B...
Ke Sun, Shikui Tu, David Yang Gao, Lei Xu