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DAWAK
2006
Springer
13 years 8 months ago
Learning Classifiers from Distributed, Ontology-Extended Data Sources
Abstract. There is an urgent need for sound approaches to integrative and collaborative analysis of large, autonomous (and hence, inevitably semantically heterogeneous) data source...
Doina Caragea, Jun Zhang 0002, Jyotishman Pathak, ...
ICML
2010
IEEE
13 years 5 months ago
OTL: A Framework of Online Transfer Learning
In this paper, we investigate a new machine learning framework called Online Transfer Learning (OTL) that aims to transfer knowledge from some source domain to an online learning ...
Peilin Zhao, Steven C. H. Hoi
SDM
2012
SIAM
252views Data Mining» more  SDM 2012»
11 years 7 months ago
Learning from Heterogeneous Sources via Gradient Boosting Consensus
Multiple data sources containing different types of features may be available for a given task. For instance, users’ profiles can be used to build recommendation systems. In a...
Xiaoxiao Shi, Jean-François Paiement, David...
OTM
2010
Springer
13 years 2 months ago
RDF Containers - A Framework for the Integration of Distributed and Heterogeneous Applications
Current trends like globalization and virtual enterprises result in an increasing need for on-the-fly integration of distributed applications grown over the past decades and origin...
Richard Mordinyi, Thomas Moser, Martin Murth, eva ...
COOPIS
2004
IEEE
13 years 8 months ago
Learning Classifiers from Semantically Heterogeneous Data
Semantically heterogeneous and distributed data sources are quite common in several application domains such as bioinformatics and security informatics. In such a setting, each dat...
Doina Caragea, Jyotishman Pathak, Vasant Honavar