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» Classes and clusters in data analysis
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ML
2010
ACM
193views Machine Learning» more  ML 2010»
15 years 1 months ago
On the eigenvectors of p-Laplacian
Spectral analysis approaches have been actively studied in machine learning and data mining areas, due to their generality, efficiency, and rich theoretical foundations. As a natur...
Dijun Luo, Heng Huang, Chris H. Q. Ding, Feiping N...
BMCBI
2007
194views more  BMCBI 2007»
15 years 6 months ago
Kernel-imbedded Gaussian processes for disease classification using microarray gene expression data
Background: Designing appropriate machine learning methods for identifying genes that have a significant discriminating power for disease outcomes has become more and more importa...
Xin Zhao, Leo Wang-Kit Cheung
DAWAK
2006
Springer
15 years 10 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, ...
VISUALIZATION
1995
IEEE
15 years 10 months ago
Recursive Pattern: A Technique for Visualizing Very Large Amounts of Data
Animportantgoalofvisualizationtechnologyistosupport the exploration and analysis of very large amounts of data. In this paper, we propose a new visualization technique called ‘r...
Daniel A. Keim, Mihael Ankerst, Hans-Peter Kriegel
NIPS
2008
15 years 8 months ago
Unlabeled data: Now it helps, now it doesn't
Empirical evidence shows that in favorable situations semi-supervised learning (SSL) algorithms can capitalize on the abundance of unlabeled training data to improve the performan...
Aarti Singh, Robert D. Nowak, Xiaojin Zhu