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Representation Learning: A Statistical Perspective
[article]
2019
arXiv
pre-print
Learning representations of data is an important problem in statistics and machine learning. While the origin of learning representations can be traced back to factor analysis and multidimensional scaling in statistics, it has become a central theme in deep learning with important applications in computer vision and computational neuroscience. In this article, we review recent advances in learning representations from a statistical perspective. In particular, we review the following two themes:
arXiv:1911.11374v1
fatcat:uo47fvw4xndnhm35kr2vjrolpi