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» Learning Mappings with Neural Network
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IJCNN
2006
IEEE
15 years 10 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 11 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 5 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 9 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
158
Voted
TKDE
2008
114views more  TKDE 2008»
15 years 4 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...