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» An Algebraic Approach to Inductive Learning
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CBMS
2005
IEEE
13 years 9 months ago
Local Dimensionality Reduction within Natural Clusters for Medical Data Analysis
Inductive learning systems have been successfully applied in a number of medical domains. Nevertheless, the effective use of these systems requires data preprocessing before apply...
Mykola Pechenizkiy, Alexey Tsymbal, Seppo Puuronen
IJCAI
2003
13 years 9 months ago
Spaces of Theories with Ideal Refinement Operators
Refinement operators for theories avoid the problems related to the myopia of many relational learning algorithms based on the operators that refine single clauses. However, the n...
Nicola Fanizzi, Stefano Ferilli, Nicola Di Mauro, ...
SAC
2006
ACM
14 years 1 months ago
The impact of sample reduction on PCA-based feature extraction for supervised learning
“The curse of dimensionality” is pertinent to many learning algorithms, and it denotes the drastic raise of computational complexity and classification error in high dimension...
Mykola Pechenizkiy, Seppo Puuronen, Alexey Tsymbal
IJCINI
2007
125views more  IJCINI 2007»
13 years 7 months ago
A Unified Approach To Fractal Dimensions
The Cognitive Processes of Abstraction and Formal Inferences J. A. Anderson: A Brain-Like Computer for Cognitive Software Applications: the Resatz Brain Project L. Flax: Cognitive ...
Witold Kinsner
ICML
2009
IEEE
14 years 8 months ago
Learning spectral graph transformations for link prediction
We present a unified framework for learning link prediction and edge weight prediction functions in large networks, based on the transformation of a graph's algebraic spectru...
Andreas Lommatzsch, Jérôme Kunegis