The Limitation and Practical Acceleration of Stochastic Gradient Algorithms in Inverse Problems

In this work we investigate the practicability of stochastic gradient descent and recently introduced variants with variance-reduction techniques in imaging inverse problems, such as space-varying image deblurring. Such algorithms have been shown in machine learning literature to have optimal comple...

Full description

Bibliographic Details

Published in:	Proceedings of the ... IEEE International Conference on Acoustics, Speech and Signal Processing (1998) pp. 7680 - 7684
Main Authors:	Tang, Junqi, Egiazarian, Karen, Davies, Mike
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01.05.2019
Subjects:	Acceleration Convergence Gradient methods Image Processing Inverse problems Machine learning Stochastic Optimization Task analysis
ISSN:	2379-190X
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!