Rank priors for continuous non-linear dimensionality reduction

Discovering the underlying low-dimensional latent structure in high-dimensional perceptual observations (e.g., images, video) can, in many cases, greatly improve performance in recognition and tracking. However, non-linear dimensionality reduction methods are often susceptible to local minima and pe...

Full description

Bibliographic Details
Main Authors: Darrell, Trevor J., Urtasun, Raquel, Geiger, Andreas
Other Authors: Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Format: Article
Language:en_US
Published: Institute of Electrical and Electronics Engineers 2010
Online Access:http://hdl.handle.net/1721.1/59287