Fast dictionary learning from incomplete data
Abstract This paper extends the recently proposed and theoretically justified iterative thresholding and K residual means (ITKrM) algorithm to learning dictionaries from incomplete/masked training data (ITKrMM). It further adapts the algorithm to the presence of a low-rank component in the data and...
Main Authors: | Valeriya Naumova, Karin Schnass |
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Format: | Article |
Language: | English |
Published: |
SpringerOpen
2018-02-01
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Series: | EURASIP Journal on Advances in Signal Processing |
Subjects: | |
Online Access: | http://link.springer.com/article/10.1186/s13634-018-0533-0 |
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