Variance Reduced Random Relaxed Projection Method for Constrained Finite-Sum Minimization Problems-Reference-Cited by-同舟云学术

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Variance Reduced Random Relaxed Projection Method for Constrained Finite-Sum Minimization Problems

Published:2024 Issue: Volume:72 Page:2188-2203
ISSN:1053-587X
Container-title:IEEE Transactions on Signal Processing
language:
Short-container-title:IEEE Trans. Signal Process.

Author:

Yang Zhichun¹^ORCID,Xia Fu-quan¹^ORCID,Tu Kai²^ORCID,Yue Man-Chung³^ORCID

Affiliation:

1. School of Mathematical Sciences, Sichuan Normal University, Chengdu, China

2. School of Mathematical Sciences, Shenzhen University, Shenzhen, China

3. Musketeers Foundation Institute of Data Science and Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, Hong Kong, China

Funder

National Natural Science Foundation of China

Hong Kong Research Grants Council

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/78/10347386/10495175.pdf?arnumber=10495175

Reference44 articles.

1. Algorithms for Fitting the Constrained Lasso

2. An Efficient Augmented Lagrangian-Based Method for Linear Equality-Constrained Lasso

3. The generalized lasso is reducible to a subspace constrained lasso

4. A New Approach to Linear Filtering and Prediction Problems

5. $\ell_1$ Trend Filtering

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