Pub Date : 2024-09-13DOI: 10.1080/10556788.2024.2400705
Chee-Khian Sim
In the literature, besides the assumption of strict complementarity, superlinear convergence of implementable polynomial-time interior point algorithms using known search directions, namely, the HK...
{"title":"Superlinear convergence of an interior point algorithm on linear semi-definite feasibility problems","authors":"Chee-Khian Sim","doi":"10.1080/10556788.2024.2400705","DOIUrl":"https://doi.org/10.1080/10556788.2024.2400705","url":null,"abstract":"In the literature, besides the assumption of strict complementarity, superlinear convergence of implementable polynomial-time interior point algorithms using known search directions, namely, the HK...","PeriodicalId":54673,"journal":{"name":"Optimization Methods & Software","volume":"152 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142178605","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-13DOI: 10.1080/10556788.2024.2396297
Robert X. Gottlieb, Pengfei Xu, Matthew D. Stuber
Trends over the past two decades indicate that much of the performance gains of commercial optimization solvers is due to improvements in x86 hardware. To continue making progress, it is critical t...
过去二十年的趋势表明，商业优化求解器的性能提升主要归功于 x86 硬件的改进。要想继续取得进展，关键是...
{"title":"Automatic source code generation for deterministic global optimization with parallel architectures","authors":"Robert X. Gottlieb, Pengfei Xu, Matthew D. Stuber","doi":"10.1080/10556788.2024.2396297","DOIUrl":"https://doi.org/10.1080/10556788.2024.2396297","url":null,"abstract":"Trends over the past two decades indicate that much of the performance gains of commercial optimization solvers is due to improvements in x86 hardware. To continue making progress, it is critical t...","PeriodicalId":54673,"journal":{"name":"Optimization Methods & Software","volume":"54 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142255600","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-14DOI: 10.1080/10556788.2024.2380688
Tran Ngoc Thang, Dao Minh Hoang, Nguyen Viet Dung
The article proposes an exact approach to finding the global solution of a nonconvex semivectorial bilevel optimization problem, where the objective functions at each level are pseudoconvex, and th...
{"title":"A neurodynamic approach for a class of pseudoconvex semivectorial bilevel optimization problems","authors":"Tran Ngoc Thang, Dao Minh Hoang, Nguyen Viet Dung","doi":"10.1080/10556788.2024.2380688","DOIUrl":"https://doi.org/10.1080/10556788.2024.2380688","url":null,"abstract":"The article proposes an exact approach to finding the global solution of a nonconvex semivectorial bilevel optimization problem, where the objective functions at each level are pseudoconvex, and th...","PeriodicalId":54673,"journal":{"name":"Optimization Methods & Software","volume":"36 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142178606","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This work elaborates on the TRust-region-ish (TRish) algorithm, a stochastic optimization method for finite-sum minimization problems proposed by Curtis et al. in [F.E. Curtis, K. Scheinberg, and R...
这项工作详细阐述了 TRust-region-ish (TRish) 算法，这是柯蒂斯等人在[F.E. Curtis, K. Scheinberg, and R...] [F.E.柯蒂斯、K. Scheinberg 和 R...] 中提出的一种用于有限和最小化问题的随机优化方法。
{"title":"An investigation of stochastic trust-region based algorithms for finite-sum minimization","authors":"Stefania Bellavia, Benedetta Morini, Simone Rebegoldi","doi":"10.1080/10556788.2024.2346834","DOIUrl":"https://doi.org/10.1080/10556788.2024.2346834","url":null,"abstract":"This work elaborates on the TRust-region-ish (TRish) algorithm, a stochastic optimization method for finite-sum minimization problems proposed by Curtis et al. in [F.E. Curtis, K. Scheinberg, and R...","PeriodicalId":54673,"journal":{"name":"Optimization Methods & Software","volume":"12544 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141944249","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-29DOI: 10.1080/10556788.2024.2339221
Aidan Epperly, Eric Evert, J. William Helton, Igor Klep
Free spectrahedra are dimension free solution sets to linear matrix inequalities of the form LA(X)=Id⊗In+A1⊗X1+A2⊗X2+⋯+Ag⊗Xg⪰0, where the Ai and Xi are symmetric matrices and the Xi have any size ...
自由谱是形式为 LA(X)=Id⊗In+A1⊗X1+A2⊗X2+⋯+Ag⊗Xg⪰0 的线性矩阵不等式的无维解集，其中 Ai 和 Xi 是对称矩阵，且 Xi 的大小不限 ...
{"title":"Matrix extreme points and free extreme points of free spectrahedra","authors":"Aidan Epperly, Eric Evert, J. William Helton, Igor Klep","doi":"10.1080/10556788.2024.2339221","DOIUrl":"https://doi.org/10.1080/10556788.2024.2339221","url":null,"abstract":"Free spectrahedra are dimension free solution sets to linear matrix inequalities of the form LA(X)=Id⊗In+A1⊗X1+A2⊗X2+⋯+Ag⊗Xg⪰0, where the Ai and Xi are symmetric matrices and the Xi have any size ...","PeriodicalId":54673,"journal":{"name":"Optimization Methods & Software","volume":"40 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141944250","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-29DOI: 10.1080/10556788.2024.2372303
Nantu Kumar Bisui, Geetanjali Panda
In this paper, a numerical approximation method is developed to find approximate solutions to a class of constrained multi-objective optimization problems. All the functions of the problem are not ...
本文开发了一种数值逼近方法，用于寻找一类受约束多目标优化问题的近似解。问题的所有函数都不是 ...
{"title":"A trust-region scheme for constrained multi-objective optimization problems with superlinear convergence property","authors":"Nantu Kumar Bisui, Geetanjali Panda","doi":"10.1080/10556788.2024.2372303","DOIUrl":"https://doi.org/10.1080/10556788.2024.2372303","url":null,"abstract":"In this paper, a numerical approximation method is developed to find approximate solutions to a class of constrained multi-objective optimization problems. All the functions of the problem are not ...","PeriodicalId":54673,"journal":{"name":"Optimization Methods & Software","volume":"14 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141869309","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-25DOI: 10.1080/10556788.2024.2381214
Shengchao Zhao, Yongchao Liu
The paper studies the distributed stochastic compositional optimization problems over networks, where all the agents' inner-level function is the sum of each agent's private expectation function. F...
{"title":"Numerical methods for distributed stochastic compositional optimization problems with aggregative structure","authors":"Shengchao Zhao, Yongchao Liu","doi":"10.1080/10556788.2024.2381214","DOIUrl":"https://doi.org/10.1080/10556788.2024.2381214","url":null,"abstract":"The paper studies the distributed stochastic compositional optimization problems over networks, where all the agents' inner-level function is the sum of each agent's private expectation function. F...","PeriodicalId":54673,"journal":{"name":"Optimization Methods & Software","volume":"47 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141869336","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-24DOI: 10.1080/10556788.2024.2380684
Abdoulaye Koroko, Ani Anciaux-Sedrakian, Ibtihel Ben Gharbia, Valérie Garès, Mounir Haddou, Quang Huy Tran
As a second-order method, the Natural Gradient Descent (NGD) has the ability to accelerate training of neural networks. However, due to the prohibitive computational and memory costs of computing a...
{"title":"Analysis and comparison of two-level KFAC methods for training deep neural networks","authors":"Abdoulaye Koroko, Ani Anciaux-Sedrakian, Ibtihel Ben Gharbia, Valérie Garès, Mounir Haddou, Quang Huy Tran","doi":"10.1080/10556788.2024.2380684","DOIUrl":"https://doi.org/10.1080/10556788.2024.2380684","url":null,"abstract":"As a second-order method, the Natural Gradient Descent (NGD) has the ability to accelerate training of neural networks. However, due to the prohibitive computational and memory costs of computing a...","PeriodicalId":54673,"journal":{"name":"Optimization Methods & Software","volume":"17 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141969317","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-24DOI: 10.1080/10556788.2024.2372668
M. Loreto, T. Humphries, C. Raghavan, K. Wu, S. Kwak
A new spectral conjugate subgradient method is presented to solve nonsmooth unconstrained optimization problems. The method combines the spectral conjugate gradient method for smooth problems with ...
{"title":"A new spectral conjugate subgradient method with application in computed tomography image reconstruction","authors":"M. Loreto, T. Humphries, C. Raghavan, K. Wu, S. Kwak","doi":"10.1080/10556788.2024.2372668","DOIUrl":"https://doi.org/10.1080/10556788.2024.2372668","url":null,"abstract":"A new spectral conjugate subgradient method is presented to solve nonsmooth unconstrained optimization problems. The method combines the spectral conjugate gradient method for smooth problems with ...","PeriodicalId":54673,"journal":{"name":"Optimization Methods & Software","volume":"74 1","pages":""},"PeriodicalIF":2.2,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141869337","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-23DOI: 10.1080/10556788.2024.2380697
Bo-Ya Zhang, Qing-Rui He, Chun-Rong Chen, Sheng-Jie Li, Ming-Hua Li
This paper attempts to propose Dai–Liao (DL)-type nonlinear conjugate gradient (CG) methods for solving vector optimization problems. Four variants of the DL method are extended and analysed from t...
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