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» Learning in FOL with a Similarity Measure
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VLDB
2003
ACM
165views Database» more  VLDB 2003»
16 years 6 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...
ESANN
2006
15 years 7 months ago
Margin based Active Learning for LVQ Networks
In this article, we extend a local prototype-based learning model by active learning, which gives the learner the capability to select training samples during the model adaptation...
Frank-Michael Schleif, Barbara Hammer, Thomas Vill...
MMM
2009
Springer
186views Multimedia» more  MMM 2009»
16 years 1 months ago
A New Multiple Kernel Approach for Visual Concept Learning
In this paper, we present a novel multiple kernel method to learn the optimal classification function for visual concept. Although many carefully designed kernels have been propose...
Jingjing Yang, Yuanning Li, YongHong Tian, Lingyu ...
IVC
2007
176views more  IVC 2007»
15 years 6 months ago
Kernel-based distance metric learning for content-based image retrieval
ct 8 For a specific set of features chosen for representing images, the performance of a content-based image retrieval (CBIR) system 9 depends critically on the similarity or diss...
Hong Chang, Dit-Yan Yeung
KDD
2004
ACM
132views Data Mining» more  KDD 2004»
16 years 6 months ago
A probabilistic framework for semi-supervised clustering
Unsupervised clustering can be significantly improved using supervision in the form of pairwise constraints, i.e., pairs of instances labeled as belonging to same or different clu...
Sugato Basu, Mikhail Bilenko, Raymond J. Mooney