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» Some Results on Greedy Embeddings in Metric Spaces
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CVPR
2008
IEEE
14 years 11 months ago
Classification via semi-Riemannian spaces
In this paper, we develop a geometric framework for linear or nonlinear discriminant subspace learning and classification. In our framework, the structures of classes are conceptu...
Deli Zhao, Zhouchen Lin, Xiaoou Tang
JSYML
2000
76views more  JSYML 2000»
14 years 9 months ago
Located Sets and Reverse Mathematics
Let X be a compact metric space. A closed set K X is located if the distance function d(x, K) exists as a continuous realvalued function on X; weakly located if the predicate d(x,...
Mariagnese Giusto, Stephen G. Simpson
BIOINFORMATICS
2008
172views more  BIOINFORMATICS 2008»
14 years 9 months ago
Fitting a geometric graph to a protein-protein interaction network
Motivation: Finding a good network null model for protein-protein interaction (PPI) networks is a fundamental issue. Such a model would provide insights into the interplay between...
Desmond J. Higham, Marija Rasajski, Natasa Przulj
ICML
2005
IEEE
15 years 10 months ago
Large margin non-linear embedding
It is common in classification methods to first place data in a vector space and then learn decision boundaries. We propose reversing that process: for fixed decision boundaries, ...
Alexander Zien, Joaquin Quiñonero Candela
JANCL
2002
77views more  JANCL 2002»
14 years 9 months ago
Axiomatizing Distance Logics
In [8, 6] we introduced a family of `modal' languages intended for talking about distances. These languages are interpreted in `distance spaces' which satisfy some (or a...
Oliver Kutz, Holger Sturm, Nobu-Yuki Suzuki, Frank...