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» An Algorithm for Learning Abductive Rules
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ICML
2007
IEEE
14 years 8 months ago
On one method of non-diagonal regularization in sparse Bayesian learning
In the paper we propose a new type of regularization procedure for training sparse Bayesian methods for classification. Transforming Hessian matrix of log-likelihood function to d...
Dmitry Kropotov, Dmitry Vetrov
ESANN
2006
13 years 9 months ago
Independent dynamics subspace analysis
Abstract. The paper presents an algorithm for identifying the independent subspace analysis model based on source dynamics. We propose to separate subspaces by decoupling their dyn...
Alexander Ilin
IJON
2002
130views more  IJON 2002»
13 years 7 months ago
Error-backpropagation in temporally encoded networks of spiking neurons
For a network of spiking neurons that encodes information in the timing of individual spike times, we derive a supervised learning rule, SpikeProp, akin to traditional errorbackpr...
Sander M. Bohte, Joost N. Kok, Johannes A. La Pout...
VW
1998
Springer
174views Virtual Reality» more  VW 1998»
14 years 7 days ago
ALife Meets Web: Lessons Learned
Arti cial life might come to play important roles for the World Wide Web, both as a source of new algorithmic paradigms and as a source of inspiration for its future development. N...
Luigi Pagliarini, Ariel Dolan, Filippo Menczer, He...
EMO
2009
Springer
159views Optimization» more  EMO 2009»
14 years 2 months ago
Recombination for Learning Strategy Parameters in the MO-CMA-ES
The multi-objective covariance matrix adaptation evolution strategy (MO-CMA-ES) is a variable-metric algorithm for real-valued vector optimization. It maintains a parent population...
Thomas Voß, Nikolaus Hansen, Christian Igel