440 search results - page 1 / 88 » Learning the structure of manifolds using random projections |
NIPS
2007
13 years 6 months ago
2007
We present a simple variant of the k-d tree which automatically adapts to intrinsic low dimensional structure in data.
NIPS
2007
13 years 6 months ago
2007
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...
MICCAI
2009
Springer
13 years 12 months ago
2009
Springer
This paper investigates an approach to model the space of brain images through a low-dimensional manifold. A data driven method to learn a manifold from a collections of brain imag...
AAAI
2008
13 years 7 months ago
2008
Most manifold learning methods consider only one similarity matrix to induce a low-dimensional manifold embedded in data space. In practice, however, we often use multiple sensors...
TIP
2010
12 years 11 months ago
2010
The emergence of low-cost sensing architectures for diverse modalities has made it possible to deploy sensor networks that capture a single event from a large number of vantage po...