A stochastic primal–dual algorithm for composite optimization with a linear operator
This paper introduces a stochastic primal–dual algorithm tailored for solving optimization problems involving the sum of three functions with a linear operator. Additionally, we conduct a comprehensive analysis of the convergence of our proposed algorithm within a generally convex framework. Our stu...
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| Published in: | Expert systems with applications Vol. 267; p. 126021 |
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| Abstract | This paper introduces a stochastic primal–dual algorithm tailored for solving optimization problems involving the sum of three functions with a linear operator. Additionally, we conduct a comprehensive analysis of the convergence of our proposed algorithm within a generally convex framework. Our study includes numerical experiments focusing on fused logistic regression and graph-guided regularized logistic regression problems. The results demonstrate that our algorithm outperforms other state-of-the-art methods in terms of efficiency and consistency.
•Design a new stochastic primal–dual algorithm for solving Non-smooth optimization problems.•Conduct a comprehensive analysis of the convergence of our proposed algorithm.•Illustrate the efficiency of our proposed algorithm through some numerical example. |
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| AbstractList | This paper introduces a stochastic primal–dual algorithm tailored for solving optimization problems involving the sum of three functions with a linear operator. Additionally, we conduct a comprehensive analysis of the convergence of our proposed algorithm within a generally convex framework. Our study includes numerical experiments focusing on fused logistic regression and graph-guided regularized logistic regression problems. The results demonstrate that our algorithm outperforms other state-of-the-art methods in terms of efficiency and consistency.
•Design a new stochastic primal–dual algorithm for solving Non-smooth optimization problems.•Conduct a comprehensive analysis of the convergence of our proposed algorithm.•Illustrate the efficiency of our proposed algorithm through some numerical example. |
| ArticleNumber | 126021 |
| Author | Tang, Yuchao Cui, Angang Zhang, Yongqiang Peng, Jigen Wen, Meng |
| Author_xml | – sequence: 1 givenname: Meng orcidid: 0000-0002-9911-3245 surname: Wen fullname: Wen, Meng email: wen5495688@163.com organization: School of Science, Xi’an Polytechnic University, Xi’an, 710048, PR China – sequence: 2 givenname: Yongqiang surname: Zhang fullname: Zhang, Yongqiang organization: College of Materials Science and Engineering, Xi’an Shiyou University, Xi’an, 710065, PR China – sequence: 3 givenname: Yuchao surname: Tang fullname: Tang, Yuchao organization: School of Mathematics and Information Science, Guangzhou University, Guangzhou, 510006, PR China – sequence: 4 givenname: Angang surname: Cui fullname: Cui, Angang organization: School of Mathematics and Statistics, Yulin University, Yulin, 719000, PR China – sequence: 5 givenname: Jigen surname: Peng fullname: Peng, Jigen organization: School of Mathematics and Information Science, Guangzhou University, Guangzhou, 510006, PR China |
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| Cites_doi | 10.1137/130919362 10.1137/110848876 10.1109/TAC.2023.3301289 10.1109/TSP.2023.3250839 10.1214/aoms/1177729586 10.1007/s10107-010-0434-y 10.1007/s10915-018-0680-3 10.1137/070704277 10.1111/j.1467-9868.2005.00490.x |
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| Keywords | 90C25 Three-operator splitting 49M29 65K10 Stochastic algorithm 49M27 47H05 Compositely optimization Primal–dual algorithm |
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Series B. Statistical Methodology doi: 10.1111/j.1467-9868.2005.00490.x – start-page: 765 year: 2018 ident: 10.1016/j.eswa.2024.126021_b23 article-title: Stochastic three-composite convex minimization with a linear operator |
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| SubjectTerms | Compositely optimization Primal–dual algorithm Stochastic algorithm Three-operator splitting |
| Title | A stochastic primal–dual algorithm for composite optimization with a linear operator |
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