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» On Generalization by Neural Networks
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140
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ACSC
2008
IEEE
15 years 5 months ago
An investigation of the state formation and transition limitations for prediction problems in recurrent neural networks
Recurrent neural networks are able to store information about previous as well as current inputs. This "memory" allows them to solve temporal problems such as language r...
Angel Kennedy, Cara MacNish
131
Voted
AAAI
1994
15 years 5 months ago
Parsing Embedded Clauses with Distributed Neural Networks
A distributed neural network model called SPEC for processing sentences with recursive relative clauses is described. The model is based on separating the tasks of segmenting the ...
Risto Miikkulainen, Dennis Bijwaard
147
Voted
ISNN
2005
Springer
15 years 9 months ago
Feature Selection and Intrusion Detection Using Hybrid Flexible Neural Tree
Current Intrusion Detection Systems (IDS) examine all data features to detect intrusion or misuse patterns. Some of the features may be redundant or contribute little (if anything)...
Yuehui Chen, Ajith Abraham, Ju Yang
134
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AMC
2008
99views more  AMC 2008»
15 years 3 months ago
Markov chain network training and conservation law approximations: Linking microscopic and macroscopic models for evolution
In this paper, a general framework for the analysis of a connection between the training of artificial neural networks via the dynamics of Markov chains and the approximation of c...
Roderick V. N. Melnik
144
Voted
ICRA
1998
IEEE
142views Robotics» more  ICRA 1998»
15 years 8 months ago
Lagrangian Relaxation Neural Networks for Job Shop Scheduling
Abstract--Manufacturing scheduling is an important but difficult task. In order to effectively solve such combinatorial optimization problems, this paper presents a novel Lagrangia...
Peter B. Luh, Xing Zhao, Yajun Wang