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» Unsupervised Nonlinear Manifold Learning
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ICANN
2003
Springer
15 years 4 months ago
Supervised Locally Linear Embedding
Locally linear embedding (LLE) is a recently proposed method for unsupervised nonlinear dimensionality reduction. It has a number of attractive features: it does not require an ite...
Dick de Ridder, Olga Kouropteva, Oleg Okun, Matti ...
PR
2006
147views more  PR 2006»
14 years 11 months ago
Robust locally linear embedding
In the past few years, some nonlinear dimensionality reduction (NLDR) or nonlinear manifold learning methods have aroused a great deal of interest in the machine learning communit...
Hong Chang, Dit-Yan Yeung
ICPR
2004
IEEE
16 years 24 days ago
Face Recognition Based on Discriminative Manifold Learning
In this paper, a discriminative manifold learning method for face recognition is proposed which achieved the discriminative embedding the high dimensional face data into a low dim...
Kap Luk Chan, Lei Wang, Yiming Wu
IVC
2007
184views more  IVC 2007»
14 years 11 months ago
Image distance functions for manifold learning
Many natural image sets are samples of a low-dimensional manifold in the space of all possible images. When the image data set is not a linear combination of a small number of bas...
Richard Souvenir, Robert Pless
NPL
2000
88views more  NPL 2000»
14 years 11 months ago
Learning Synaptic Clusters for Nonlinear Dendritic Processing
Nonlinear dendritic processing appears to be a feature of biological neurons and would also be of use in many applications of artificial neural networks. This paper presents a mod...
Michael W. Spratling, Gillian Hayes