Fast dictionary learning from incomplete data

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...

Full description

Bibliographic Details
Main Authors: Valeriya Naumova, Karin Schnass
Format: Article
Language:English
Published: SpringerOpen 2018-02-01
Series:EURASIP Journal on Advances in Signal Processing
Subjects:
Dictionary learning
Sparse coding
Sparse component analysis
Thresholding
K-means
Erasures
Online Access:http://link.springer.com/article/10.1186/s13634-018-0533-0

Internet

http://link.springer.com/article/10.1186/s13634-018-0533-0

Similar Items