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» Evolving Artificial Neural Networks that Develop in Time
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IJCNN
2007
IEEE
15 years 3 months ago
Parallel Learning of Large Fuzzy Cognitive Maps
— Fuzzy Cognitive Maps (FCMs) are a class of discrete-time Artificial Neural Networks that are used to model dynamic systems. A recently introduced supervised learning method, wh...
Wojciech Stach, Lukasz A. Kurgan, Witold Pedrycz
PAKDD
2000
ACM
161views Data Mining» more  PAKDD 2000»
15 years 1 months ago
Adaptive Boosting for Spatial Functions with Unstable Driving Attributes
Combining multiple global models (e.g. back-propagation based neural networks) is an effective technique for improving classification accuracy by reducing a variance through manipu...
Aleksandar Lazarevic, Tim Fiez, Zoran Obradovic
KDD
2005
ACM
140views Data Mining» more  KDD 2005»
15 years 10 months ago
Graphs over time: densification laws, shrinking diameters and possible explanations
How do real graphs evolve over time? What are "normal" growth patterns in social, technological, and information networks? Many studies have discovered patterns in stati...
Jure Leskovec, Jon M. Kleinberg, Christos Faloutso...
DEXA
1998
Springer
112views Database» more  DEXA 1998»
15 years 1 months ago
Optimisation of Active Rule Agents Using a Genetic Algorithm Approach
Intelligent agents and active databases have a number of common characteristics, the most important of which is that they both execute actions by firing rules upon events occurring...
Evaggelos Nonas, Alexandra Poulovassilis
BIOSURVEILLANCE
2008
Springer
14 years 11 months ago
Dynamic Network Model for Predicting Occurrences of Salmonella at Food Facilities
Salmonella is among the most common food borne illnesses which may result from consumption of contaminated products. In this paper we model the co-occurrence data between USDA-cont...
Purnamrita Sarkar, Lujie Chen, Artur Dubrawski