Non-linear Latent Factor Models for Revealing Structure in High-dimensional Data
Real world data is not random: The variability in the data-sets that arise in computer vision, signal processing and other areas is often highly constrained and governed by a number of degrees of freedom that is much smaller than the superficial dimensionality of the data. Unsupervised learning meth...
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| Format: | Others |
| Language: | en_ca |
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2008
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| Online Access: | http://hdl.handle.net/1807/11118 |