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» Discovering Classification from Data of Multiple Sources
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KDD
2008
ACM
181views Data Mining» more  KDD 2008»
14 years 8 months ago
Learning subspace kernels for classification
Kernel methods have been applied successfully in many data mining tasks. Subspace kernel learning was recently proposed to discover an effective low-dimensional subspace of a kern...
Jianhui Chen, Shuiwang Ji, Betul Ceran, Qi Li, Min...
ICMLA
2008
13 years 9 months ago
Mapping Uncharted Waters: Exploratory Analysis, Visualization, and Clustering of Oceanographic Data
In this paper we describe an interdisciplinary collaboration between researchers in machine learning and oceanography. The collaboration was formed to study the problem of open oc...
Joshua M. Lewis, Pincelli M. Hull, Kilian Q. Weinb...
DILS
2005
Springer
14 years 1 months ago
Information Integration and Knowledge Acquisition from Semantically Heterogeneous Biological Data Sources
Abstract. We present INDUS (Intelligent Data Understanding System), a federated, query-centric system for knowledge acquisition from autonomous, distributed, semantically heterogen...
Doina Caragea, Jyotishman Pathak, Jie Bao, Adrian ...
BMCBI
2008
141views more  BMCBI 2008»
13 years 7 months ago
Ontology-guided data preparation for discovering genotype-phenotype relationships
Complexity of post-genomic data and multiplicity of mining strategies are two limits to Knowledge Discovery in Databases (KDD) in life sciences. Because they provide a semantic fr...
Adrien Coulet, Malika Smaïl-Tabbone, Pascale ...
PKDD
2010
Springer
138views Data Mining» more  PKDD 2010»
13 years 6 months ago
Constructing Nonlinear Discriminants from Multiple Data Views
There are many situations in which we have more than one view of a single data source, or in which we have multiple sources of data that are aligned. We would like to be able to bu...
Tom Diethe, David R. Hardoon, John Shawe-Taylor