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» K-means clustering via principal component analysis
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BCS
2008
13 years 9 months ago
Fast Estimation of Nonparametric Kernel Density Through PDDP, and its Application in Texture Synthesis
In this work, a new algorithm is proposed for fast estimation of nonparametric multivariate kernel density, based on principal direction divisive partitioning (PDDP) of the data s...
Arnab Sinha, Sumana Gupta
KES
2007
Springer
14 years 1 months ago
Models for Identifying Structures in the Data: A Performance Comparison
This paper reports on the unsupervised analysis of seismic signals recorded in Italy, respectively on the Vesuvius volcano, located in Naples, and on the Stromboli volcano, located...
Anna Esposito, Antonietta M. Esposito, Flora Giudi...
ICCV
2009
IEEE
15 years 14 days ago
Robust Fitting of Multiple Structures: The Statistical Learning Approach
We propose an unconventional but highly effective approach to robust fitting of multiple structures by using statistical learning concepts. We design a novel Mercer kernel for t...
Tat-Jun Chin, Hanzi Wang, David Suter
ICPR
2004
IEEE
14 years 8 months ago
An Iris Image Synthesis Method Based on PCA and Super-Resolution
It is very important for the performance evaluation of iris recognition algorithms to construct very large iris databases. However, limited by the real conditions, there are no ve...
Jiali Cui, JunZhou Huang, Tieniu Tan, Yunhong Wang...
ICML
2008
IEEE
14 years 8 months ago
Expectation-maximization for sparse and non-negative PCA
We study the problem of finding the dominant eigenvector of the sample covariance matrix, under additional constraints on the vector: a cardinality constraint limits the number of...
Christian D. Sigg, Joachim M. Buhmann