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» Learning Mappings with Neural Network
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IJCNN
2006
IEEE
15 years 8 months ago
Knowledge Representation and Possible Worlds for Neural Networks
— The semantics of neural networks can be analyzed mathematically as a distributed system of knowledge and as systems of possible worlds expressed in the knowledge. Learning in a...
Michael J. Healy, Thomas P. Caudell
ICANN
2009
Springer
15 years 8 months ago
Almost Random Projection Machine
Backpropagation of errors is not only hard to justify from biological perspective but also it fails to solve problems requiring complex logic. A simpler algorithm based on generati...
Wlodzislaw Duch, Tomasz Maszczyk
NIPS
1996
15 years 3 months ago
Monotonicity Hints
: Neural networks are competitive tools for classification problems. In this context, a hint is any piece of prior side information about the classification. Common examples are mo...
Joseph Sill, Yaser S. Abu-Mostafa
NEUROSCIENCE
2001
Springer
15 years 6 months ago
Finite-State Computation in Analog Neural Networks: Steps towards Biologically Plausible Models?
Abstract. Finite-state machines are the most pervasive models of computation, not only in theoretical computer science, but also in all of its applications to real-life problems, a...
Mikel L. Forcada, Rafael C. Carrasco
TKDE
2008
114views more  TKDE 2008»
15 years 1 months ago
Neural-Based Learning Classifier Systems
UCS is a supervised learning classifier system that was introduced in 2003 for classification in data mining tasks. The representation of a rule in UCS as a univariate classificati...
Hai Huong Dam, Hussein A. Abbass, Chris Lokan, Xin...