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IJCNN
2000
IEEE
13 years 12 months ago
Continuous Optimization of Hyper-Parameters
Many machine learning algorithms can be formulated as the minimization of a training criterion which involves (1) \training errors" on each training example and (2) some hype...
Yoshua Bengio
ICANN
2010
Springer
13 years 7 months ago
Computational Properties of Probabilistic Neural Networks
We discuss the problem of overfitting of probabilistic neural networks in the framework of statistical pattern recognition. The probabilistic approach to neural networks provides a...
Jiri Grim, Jan Hora
SBRN
2000
IEEE
13 years 12 months ago
Adaptation of Parameters of BP Algorithm Using Learning Automata
d Articles >> Table of Contents >> Abstract VI Brazilian Symposium on Neural Networks (SBRN'00) p. 24 Adaptation of Parameters of BP Algorithm Using Automata Hamid...
Hamid Beigy, Mohammad Reza Meybodi
CAMAD
2006
IEEE
13 years 11 months ago
P2PRealm - peer-to-peer network simulator
Abstract--Peer-to-Peer Realm (P2PRealm) is an efficient peer-topeer network simulator for studying algorithms based on neural networks. In contrast to many simulators, which emphas...
Niko Kotilainen, Mikko Vapa, Teemu Keltanen, Annem...
GECCO
2005
Springer
155views Optimization» more  GECCO 2005»
14 years 1 months ago
Co-evolving recurrent neurons learn deep memory POMDPs
Recurrent neural networks are theoretically capable of learning complex temporal sequences, but training them through gradient-descent is too slow and unstable for practical use i...
Faustino J. Gomez, Jürgen Schmidhuber