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NECO
1998
151views more  NECO 1998»
14 years 9 months ago
Nonlinear Component Analysis as a Kernel Eigenvalue Problem
We describe a new method for performing a nonlinear form of Principal Component Analysis. By the use of integral operator kernel functions, we can e ciently compute principal comp...
Bernhard Schölkopf, Alex J. Smola, Klaus-Robe...
CVPR
2006
IEEE
15 years 12 months ago
Epipolar Geometry of Central Projection Systems Using Veronese Maps
We study the epipolar geometry between views acquired by mixtures of central projection systems including catadioptric sensors and cameras with lens distortion. Since the projecti...
João P. Barreto, Kostas Daniilidis
EOR
2006
65views more  EOR 2006»
14 years 10 months ago
Self-organizing maps could improve the classification of Spanish mutual funds
In this paper, we apply nonlinear techniques (Self-Organizing Maps, k-nearest neighbors and the k-means algorithm) to evaluate the official Spanish mutual funds classification. Th...
David Moreno, Paulina Marco, Ignacio Olmeda
KDD
2007
ACM
276views Data Mining» more  KDD 2007»
15 years 10 months ago
Nonlinear adaptive distance metric learning for clustering
A good distance metric is crucial for many data mining tasks. To learn a metric in the unsupervised setting, most metric learning algorithms project observed data to a lowdimensio...
Jianhui Chen, Zheng Zhao, Jieping Ye, Huan Liu
KDD
2004
ACM
131views Data Mining» more  KDD 2004»
15 years 10 months ago
Fast nonlinear regression via eigenimages applied to galactic morphology
Astronomy increasingly faces the issue of massive datasets. For instance, the Sloan Digital Sky Survey (SDSS) has so far generated tens of millions of images of distant galaxies, ...
Brigham Anderson, Andrew W. Moore, Andrew Connolly...