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ICPR
2000
IEEE
15 years 2 months ago
Two-Stage Computational Cost Reduction Algorithm Based on Mahalanobis Distance Approximations
For many pattern recognition methods, high recognition accuracy is obtained at very high expense of computational cost. In this paper, a new algorithm that reduces the computation...
Fang Sun, Shinichiro Omachi, Nei Kato, Hirotomo As...
ICPR
2002
IEEE
15 years 2 months ago
Determining a Suitable Metric when Using Non-Negative Matrix Factorization
The Non-negative Matrix Factorization technique (NMF) has been recently proposed for dimensionality reduction. NMF is capable to produce a region- or partbased representation of o...
David Guillamet, Jordi Vitrià

Publication
197views
13 years 5 months ago
Convex non-negative matrix factorization for massive datasets
Non-negative matrix factorization (NMF) has become a standard tool in data mining, information retrieval, and signal processing. It is used to factorize a non-negative data matrix ...
C. Thurau, K. Kersting, M. Wahabzada, and C. Bauck...
COMPGEOM
2011
ACM
14 years 1 months ago
Persistence-based clustering in riemannian manifolds
We present a clustering scheme that combines a mode-seeking phase with a cluster merging phase in the corresponding density map. While mode detection is done by a standard graph-b...
Frédéric Chazal, Leonidas J. Guibas,...
KDD
2008
ACM
172views Data Mining» more  KDD 2008»
15 years 10 months ago
Structured metric learning for high dimensional problems
The success of popular algorithms such as k-means clustering or nearest neighbor searches depend on the assumption that the underlying distance functions reflect domain-specific n...
Jason V. Davis, Inderjit S. Dhillon