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ICML
2005
IEEE
16 years 4 months ago
Clustering through ranking on manifolds
Clustering aims to find useful hidden structures in data. In this paper we present a new clustering algorithm that builds upon the consistency method (Zhou, et.al., 2003), a semi-...
Markus Breitenbach, Gregory Z. Grudic
ITS
1998
Springer
107views Multimedia» more  ITS 1998»
15 years 7 months ago
Toward a Unification of Human-Computer Learning and Tutoring
We define a learning tutor as being an intelligent agent that learns from human tutors and then tutors human learners. The notion of a learning tutor provides a conceptual framewor...
Henry Hamburger, Gheorghe Tecuci
ICML
2007
IEEE
16 years 4 months ago
Discriminant analysis in correlation similarity measure space
Correlation is one of the most widely used similarity measures in machine learning like Euclidean and Mahalanobis distances. However, compared with proposed numerous discriminant ...
Yong Ma, Shihong Lao, Erina Takikawa, Masato Kawad...
ML
2008
ACM
15 years 3 months ago
A bias/variance decomposition for models using collective inference
Bias/variance analysis is a useful tool for investigating the performance of machine learning algorithms. Conventional analysis decomposes loss into errors due to aspects of the le...
Jennifer Neville, David Jensen
EMNLP
2009
15 years 1 months ago
Reverse Engineering of Tree Kernel Feature Spaces
We present a framework to extract the most important features (tree fragments) from a Tree Kernel (TK) space according to their importance in the target kernelbased machine, e.g. ...
Daniele Pighin, Alessandro Moschitti