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» A Comparative Study of Fuzzy Sets and Rough Sets
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IJCNN
2008
IEEE
16 years 20 days ago
A comparison of fuzzy ARTMAP and Gaussian ARTMAP neural networks for incremental learning
Abstract— Automatic pattern classifiers that allow for incremental learning can adapt internal class models efficiently in response to new information, without having to retrai...
Eric Granger, Jean-François Connolly, Rober...
ENGL
2007
89views more  ENGL 2007»
15 years 6 months ago
Similarity-based Heterogeneous Neural Networks
This research introduces a general class of functions serving as generalized neuron models to be used in artificial neural networks. They are cast in the common framework of comp...
Lluís A. Belanche Muñoz, Julio Jose ...
CICLING
2010
Springer
15 years 10 months ago
Automatic Generation of Bilingual Dictionaries Using Intermediary Languages and Comparable Corpora
Abstract. This paper outlines a strategy to build new bilingual dictionaries from existing resources. The method is based on two main tasks: first, a new set of bilingual correspo...
Pablo Gamallo Otero, José Ramon Pichel Camp...
SAC
2010
ACM
16 years 1 months ago
Design pattern implementation in object teams
Implementing the 23 Gang-of-Four design patterns in the aspectoriented programming language Object Teams/Java (OT/J) yields modularity and reusability results roughly comparable t...
João L. Gomes, Miguel P. Monteiro
COLT
2008
Springer
15 years 8 months ago
Does Unlabeled Data Provably Help? Worst-case Analysis of the Sample Complexity of Semi-Supervised Learning
We study the potential benefits to classification prediction that arise from having access to unlabeled samples. We compare learning in the semi-supervised model to the standard, ...
Shai Ben-David, Tyler Lu, Dávid Pál