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» Learning Rule Representations from Boolean Data
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102
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ICALP
2009
Springer
16 years 22 days ago
Testing Fourier Dimensionality and Sparsity
We present a range of new results for testing properties of Boolean functions that are defined in terms of the Fourier spectrum. Broadly speaking, our results show that the propert...
Parikshit Gopalan, Ryan O'Donnell, Rocco A. Served...
CIBB
2008
15 years 2 months ago
Mining Association Rule Bases from Integrated Genomic Data and Annotations
During the last decade, several clustering and association rule mining techniques have been applied to highlight groups of coregulated genes in gene expression data. Nowadays, inte...
Ricardo Martínez, Nicolas Pasquier, Claude ...
77
Voted
FUZZIEEE
2007
IEEE
15 years 6 months ago
Learning Fuzzy Linguistic Models from Low Quality Data by Genetic Algorithms
— Incremental rule base learning techniques can be used to learn models and classifiers from interval or fuzzyvalued data. These algorithms are efficient when the observation e...
Luciano Sánchez, José Otero
HPCS
2006
IEEE
15 years 6 months ago
Grid-Enabling the Global Geodynamics Project: Automatic RDF Extraction from the ESML Data Description and Representation via GRD
An eXtensible Markup Language (XML) based data model for the Global Geodynamics Project (GGP) has been previously developed. Mindful of the need to incorporate metadata into the d...
L. Ian Lumb, Keith D. Aldridge
83
Voted
KDD
2004
ACM
314views Data Mining» more  KDD 2004»
16 years 26 days ago
Assessment of discretization techniques for relevant pattern discovery from gene expression data
In the domain of gene expression data analysis, various researchers have recently emphasized the promising application of pattern discovery techniques like association rule mining...
Ruggero G. Pensa, Claire Leschi, Jéré...