Discovery of Latent Factors in High-dimensional Data Using Tensor Methods
<p>Unsupervised learning aims at the discovery of hidden structure that drives the observations in the real world. It is essential for success in modern machine learning and artificial intelligence. Latent variable models are versatile in unsupervised learning and have applications in almost e...
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| Language: | EN |
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University of California, Irvine
2016
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| Online Access: | http://pqdtopen.proquest.com/#viewpdf?dispub=10125323 |