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» Learning Classifiers from Semantically Heterogeneous Data
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GCB
2010
Springer
204views Biometrics» more  GCB 2010»
13 years 5 months ago
Learning Pathway-based Decision Rules to Classify Microarray Cancer Samples
: Despite recent advances in DNA chip technology current microarray gene expression studies are still affected by high noise levels, small sample sizes and large numbers of uninfor...
Enrico Glaab, Jonathan M. Garibaldi, Natalio Krasn...
ISSADS
2005
Springer
14 years 1 months ago
Database System Architecture - A Walk Through Time: From Centralized Platform to Mobile Computing - Keynote Address
Classical distributed database systems monolithically offer distribution transparency and higher performance. This is made possible by making data available and closer to the appl...
Ali R. Hurson, Yu Jiao
GEOINFO
2004
13 years 9 months ago
Ontology-driven Resolution of Semantic Heterogeneities in GDB Conceptual Schemas
: As the geographic information system (GIS) community grows, more and more people needs to share geographic information. As modern GIS data is stored in geographic databases their...
Guillermo Nudelman Hess, Cirano Iochpe
ESWS
2008
Springer
13 years 9 months ago
Adding Data Mining Support to SPARQL Via Statistical Relational Learning Methods
Exploiting the complex structure of relational data enables to build better models by taking into account the additional information provided by the links between objects. We exten...
Christoph Kiefer, Abraham Bernstein, André ...
PCM
2007
Springer
114views Multimedia» more  PCM 2007»
14 years 1 months ago
Random Convolution Ensembles
A novel method for creating diverse ensembles of image classifiers is proposed. The idea is that, for each base image classifier in the ensemble, a random image transformation is g...
Michael Mayo