Sciweavers

Free Online Productivity Tools i2Speak i2Symbol i2OCR iTex2Img iWeb2Print iWeb2Shot i2Type iPdf2Split iPdf2Merge i2Bopomofo i2Arabic i2Style i2Image i2PDF iLatex2Rtf Sci2ools

7

NIPS
2004

favoriteEmaildiscussreport

204views Information Technology» more NIPS 2004»

Adaptive Manifold Learning

13 years 5 months ago

Adaptive Manifold Learning

Download books.nips.cc

Recently, there have been several advances in the machine learning and pattern recognition communities for developing manifold learning algorithms to construct nonlinear low-dimensional manifolds from sample data points embedded in high-dimensional spaces. In this paper, we develop algorithms that address two key issues in manifold learning: 1) the adaptive selection of the neighborhood sizes; and 2) better fitting the local geometric structure to account for the variations in the curvature of the manifold and its interplay with the sampling density of the data set. We also illustrate the effectiveness of our methods on some synthetic data sets.

Jing Wang, Zhenyue Zhang, Hongyuan Zha

Real-time Traffic

Manifold | NIPS 2004 | NIPS 2007 | Nonlinear Low-dimensional Manifolds | Sample Data Points |

claim paper

Related Content

» Regularized Minimum Volume Ellipsoid Metric for QueryBased Learning

» Boosting on Manifolds Adaptive Regularization of Base Classifiers

» Adaptive Nonlinear AutoAssociative Modeling Through Manifold Learning

» Adaptive mesh compression in 3D computer graphics using multiscale manifold learning

» Learning the structure of manifolds using random projections

» Adaptive Distance Metric Learning for Clustering

» Nonisometric manifold learning analysis and an algorithm

» Hyperplane margin classifiers on the multinomial manifold

» Manifold Learning for ToFbased Human Body Tracking and Activity Recognition

Post Info
More Details (n/a)

Added	31 Oct 2010
Updated	31 Oct 2010
Type	Conference
Year	2004
Where	NIPS
Authors	Jing Wang, Zhenyue Zhang, Hongyuan Zha

Comments (0)