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» Data Clustering Using Evidence Accumulation
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CVPR
2007
IEEE
15 years 11 months ago
Adaptive Patch Features for Object Class Recognition with Learned Hierarchical Models
We present a hierarchical generative model for object recognition that is constructed by weakly-supervised learning. A key component is a novel, adaptive patch feature whose width...
Fabien Scalzo, Justus H. Piater
CIKM
2008
Springer
14 years 11 months ago
Metric-based ontology learning
Ontology learning is an important task in Artificial Intelligence, Semantic Web and Text Mining. This paper presents a novel framework for, and solutions to, three practical probl...
Hui Yang, Jamie Callan
ISSTA
2007
ACM
14 years 11 months ago
Experimental assessment of random testing for object-oriented software
Progress in testing requires that we evaluate the effectiveness of testing strategies on the basis of hard experimental evidence, not just intuition or a priori arguments. Random ...
Ilinca Ciupa, Andreas Leitner, Manuel Oriol, Bertr...
ICCV
2007
IEEE
15 years 11 months ago
Locally Smooth Metric Learning with Application to Image Retrieval
In this paper, we propose a novel metric learning method based on regularized moving least squares. Unlike most previous metric learning methods which learn a global Mahalanobis d...
Dit-Yan Yeung, Hong Chang
BMCBI
2008
167views more  BMCBI 2008»
14 years 9 months ago
Expression profiles of switch-like genes accurately classify tissue and infectious disease phenotypes in model-based classificat
Background: Large-scale compilation of gene expression microarray datasets across diverse biological phenotypes provided a means of gathering a priori knowledge in the form of ide...
Michael Gormley, Aydin Tozeren