Provable ICA with Unknown Gaussian Noise, and Implications for Gaussian Mixtures and Autoencoders
We present a new algorithm for independent component analysis which has provable performance guarantees. In particular, suppose we are given samples of the form y=Ax+η where A is an unknown but non-singular n×n matrix, x is a random variable whose coordinates are independent and have a fourth order...
Main Authors: | Arora, Sanjeev, Ge, Rong, Moitra, Ankur, Sachdeva, Sushant |
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Other Authors: | Massachusetts Institute of Technology. Department of Mathematics |
Format: | Article |
Language: | English |
Published: |
Springer US
2017
|
Online Access: | http://hdl.handle.net/1721.1/106898 https://orcid.org/0000-0001-7047-0495 |
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