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» Discovering Classification from Data of Multiple Sources
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CVPR
2008
IEEE
16 years 8 months ago
Unsupervised discovery of visual object class hierarchies
Objects in the world can be arranged into a hierarchy based on their semantic meaning (e.g. organism ? animal ? feline ? cat). What about defining a hierarchy based on the visual ...
Josef Sivic, Bryan C. Russell, Andrew Zisserman, W...
AAAI
2006
15 years 7 months ago
Efficient Active Fusion for Decision-Making via VOI Approximation
Active fusion is a process that purposively selects the most informative information from multiple sources as well as combines these information for achieving a reliable result ef...
Wenhui Liao, Qiang Ji
DOLAP
2008
ACM
15 years 8 months ago
Data mining-based fragmentation of XML data warehouses
With the multiplication of XML data sources, many XML data warehouse models have been proposed to handle data heterogeneity and complexity in a way relational data warehouses fail...
Hadj Mahboubi, Jérôme Darmont
IDA
2005
Springer
15 years 12 months ago
Removing Statistical Biases in Unsupervised Sequence Learning
Unsupervised sequence learning is important to many applications. A learner is presented with unlabeled sequential data, and must discover sequential patterns that characterize the...
Yoav Horman, Gal A. Kaminka
MICCAI
2009
Springer
16 years 7 months ago
MKL for Robust Multi-modality AD Classification
We study the problem of classifying mild Alzheimer's disease (AD) subjects from healthy individuals (controls) using multi-modal image data, to facilitate early identification...
Chris Hinrichs, Vikas Singh, Guofan Xu, Sterlin...