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» Neural Networks and Complexity Theory
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NIPS
1989
15 years 5 months ago
The Cascade-Correlation Learning Architecture
Cascade-Correlation is a new architecture and supervised learning algorithm for artificial neural networks. Instead of just adjusting the weights in a network of fixed topology,...
Scott E. Fahlman, Christian Lebiere
JMLR
2010
143views more  JMLR 2010»
14 years 11 months ago
Incremental Sigmoid Belief Networks for Grammar Learning
We propose a class of Bayesian networks appropriate for structured prediction problems where the Bayesian network's model structure is a function of the predicted output stru...
James Henderson, Ivan Titov
MSWIM
2005
ACM
15 years 10 months ago
YAES: a modular simulator for mobile networks
Developing network protocols for mobile wireless systems is a complex task, and most of the existing simulator frameworks are not well suited for experimental development. The YAE...
Ladislau Bölöni, Damla Turgut
EOR
2006
88views more  EOR 2006»
15 years 4 months ago
Nonessential objectives within network approaches for MCDM
In Gal and Hanne [Eur. J. Oper. Res. 119 (1999) 373] the problem of using several methods to solve a multiple criteria decision making (MCDM) problem with linear objective functio...
Tomas Gal, Thomas Hanne
IWANN
2009
Springer
15 years 11 months ago
Fuzzy Logic, Soft Computing, and Applications
We survey on the theoretical and practical developments of the theory of fuzzy logic and soft computing. Specifically, we briefly review the history and main milestones of fuzzy ...
Inma P. Cabrera, Pablo Cordero, Manuel Ojeda-Acieg...