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» Learning from Highly Structured Data by Decomposition
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VLDB
2003
ACM
165views Database» more  VLDB 2003»
15 years 10 months ago
Learning to match ontologies on the Semantic Web
On the Semantic Web, data will inevitably come from many different ontologies, and information processing across ontologies is not possible without knowing the semantic mappings be...
AnHai Doan, Jayant Madhavan, Robin Dhamankar, Pedr...
ISNN
2010
Springer
15 years 2 months ago
Applications of Second Order Blind Identification to High-Density EEG-Based Brain Imaging: A Review
In the context of relating specific brain functions to specific brain structures, second-order blind identification (SOBI) is one of the blind source separation algorithms that hav...
Akaysha Tang
BMCBI
2006
159views more  BMCBI 2006»
14 years 10 months ago
Prediction of protein continuum secondary structure with probabilistic models based on NMR solved structures
Background: The structure of proteins may change as a result of the inherent flexibility of some protein regions. We develop and explore probabilistic machine learning methods for...
Mikael Bodén, Zheng Yuan, Timothy L. Bailey
VLDB
1997
ACM
112views Database» more  VLDB 1997»
15 years 2 months ago
Selectivity Estimation Without the Attribute Value Independence Assumption
The result size of a query that involves multiple attributes from the same relation depends on these attributes’ joint data distribution,i.e., the frequencies of all combination...
Viswanath Poosala, Yannis E. Ioannidis
CVPR
2003
IEEE
16 years 21 hour ago
Learning Bayesian Network Classifiers for Facial Expression Recognition using both Labeled and Unlabeled Data
Understanding human emotions is one of the necessary skills for the computer to interact intelligently with human users. The most expressive way humans display emotions is through...
Ira Cohen, Nicu Sebe, Fabio Gagliardi Cozman, Marc...