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...
| Autors principals: | , , |
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| Altres autors: | |
| Format: | Article |
| Idioma: | en_US |
| Publicat: |
Institute of Electrical and Electronics Engineers
2010
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| Accés en línia: | http://hdl.handle.net/1721.1/59287 |
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