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NIPS
1998
13 years 9 months ago
Semi-Supervised Support Vector Machines
We introduce a semi-supervised support vector machine (S3 VM) method. Given a training set of labeled data and a working set of unlabeled data, S3 VM constructs a support vector m...
Kristin P. Bennett, Ayhan Demiriz
BC
2004
114views more  BC 2004»
13 years 7 months ago
Spike timing and synaptic plasticity in the premotor pathway of birdsong
Abstract. The neural circuits of birdsong appear to utilize specific time delays in their operation. In particular, the anterior forebrain pathway (AFP) is implicated in an approxi...
Henry D. I. Abarbanel, Leif Gibb, Gabriel B. Mindl...
CEC
2003
IEEE
13 years 11 months ago
Dynamics of gene expression in an artificial genome
Abstract- Complex systems techniques provide a powerful tool to study the emergent properties of networks of interacting genes. In this study we extract models of genetic regulator...
Kai Willadsen, Janet Wiles
TSMC
2010
13 years 2 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
CORR
2012
Springer
170views Education» more  CORR 2012»
12 years 3 months ago
What Cannot be Learned with Bethe Approximations
We address the problem of learning the parameters in graphical models when inference is intractable. A common strategy in this case is to replace the partition function with its B...
Uri Heinemann, Amir Globerson