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» An Algorithm for Intrinsic Dimensionality Estimation
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WSCG
2004
185views more  WSCG 2004»
15 years 1 months ago
Automatic Fitting and Control of Complex Freeform Shapes in 3-D
In many computer graphics and computer-aided design problems, it is very common to find a smooth and well structured surface to fit a set of unstructured 3-dimensional data. Altho...
Yu Song, Joris S. M. Vergeest, Chensheng Wang
128
Voted
PAMI
2008
391views more  PAMI 2008»
14 years 11 months ago
Riemannian Manifold Learning
Recently, manifold learning has been widely exploited in pattern recognition, data analysis, and machine learning. This paper presents a novel framework, called Riemannian manifold...
Tong Lin, Hongbin Zha
105
Voted
NIPS
2007
15 years 1 months ago
Random Projections for Manifold Learning
We propose a novel method for linear dimensionality reduction of manifold modeled data. First, we show that with a small number M of random projections of sample points in RN belo...
Chinmay Hegde, Michael B. Wakin, Richard G. Barani...
91
Voted
IBPRIA
2003
Springer
15 years 4 months ago
Supervised Locally Linear Embedding Algorithm for Pattern Recognition
The dimensionality of the input data often far exceeds their intrinsic dimensionality. As a result, it may be difficult to recognize multidimensional data, especially if the number...
Olga Kouropteva, Oleg Okun, Matti Pietikäinen
TIT
2008
141views more  TIT 2008»
14 years 11 months ago
Dimensionality Reduction for Distributed Estimation in the Infinite Dimensional Regime
Distributed estimation of an unknown signal is a common task in sensor networks. The scenario usually envisioned consists of several nodes, each making an observation correlated wi...
Olivier Roy, Martin Vetterli