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Superlinear convergence of an interior point algorithm on linear semi-definite feasibility problems 线性半有限可行性问题内点算法的超线性收敛性
IF 2.2 3区 数学
Optimization Methods & Software Pub Date : 2024-09-13 DOI: 10.1080/10556788.2024.2400705
Chee-Khian Sim
{"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":null,"pages":null},"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}
引用次数: 0
Automatic source code generation for deterministic global optimization with parallel architectures 利用并行架构自动生成确定性全局优化的源代码
IF 2.2 3区 数学
Optimization Methods & Software Pub Date : 2024-09-13 DOI: 10.1080/10556788.2024.2396297
Robert X. Gottlieb, Pengfei Xu, Matthew D. Stuber
{"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":null,"pages":null},"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}
引用次数: 0
A neurodynamic approach for a class of pseudoconvex semivectorial bilevel optimization problems 一类伪凸半矢量双层优化问题的神经动力学方法
IF 2.2 3区 数学
Optimization Methods & Software Pub Date : 2024-08-14 DOI: 10.1080/10556788.2024.2380688
Tran Ngoc Thang, Dao Minh Hoang, Nguyen Viet Dung
{"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":null,"pages":null},"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}
引用次数: 0
An investigation of stochastic trust-region based algorithms for finite-sum minimization 基于随机信任区域的有限和最小化算法研究
IF 2.2 3区 数学
Optimization Methods & Software Pub Date : 2024-08-08 DOI: 10.1080/10556788.2024.2346834
Stefania Bellavia, Benedetta Morini, Simone Rebegoldi
{"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":null,"pages":null},"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}
引用次数: 0
Matrix extreme points and free extreme points of free spectrahedra 自由光谱的矩阵极值点和自由极值点
IF 2.2 3区 数学
Optimization Methods & Software Pub Date : 2024-07-29 DOI: 10.1080/10556788.2024.2339221
Aidan Epperly, Eric Evert, J. William Helton, Igor Klep
{"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":null,"pages":null},"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}
引用次数: 0
A trust-region scheme for constrained multi-objective optimization problems with superlinear convergence property 具有超线性收敛特性的约束多目标优化问题信任区域方案
IF 2.2 3区 数学
Optimization Methods & Software Pub Date : 2024-07-29 DOI: 10.1080/10556788.2024.2372303
Nantu Kumar Bisui, Geetanjali Panda
{"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":null,"pages":null},"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}
引用次数: 0
Numerical methods for distributed stochastic compositional optimization problems with aggregative structure 具有聚合结构的分布式随机组合优化问题的数值方法
IF 2.2 3区 数学
Optimization Methods & Software Pub Date : 2024-07-25 DOI: 10.1080/10556788.2024.2381214
Shengchao Zhao, Yongchao Liu
{"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":null,"pages":null},"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}
引用次数: 0
Analysis and comparison of two-level KFAC methods for training deep neural networks 用于训练深度神经网络的两级 KFAC 方法的分析与比较
IF 2.2 3区 数学
Optimization Methods & Software Pub Date : 2024-07-24 DOI: 10.1080/10556788.2024.2380684
Abdoulaye Koroko, Ani Anciaux-Sedrakian, Ibtihel Ben Gharbia, Valérie Garès, Mounir Haddou, Quang Huy Tran
{"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":null,"pages":null},"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}
引用次数: 0
A new spectral conjugate subgradient method with application in computed tomography image reconstruction 一种新的光谱共轭子梯度法在计算机断层扫描图像重建中的应用
IF 2.2 3区 数学
Optimization Methods & Software Pub Date : 2024-07-24 DOI: 10.1080/10556788.2024.2372668
M. Loreto, T. Humphries, C. Raghavan, K. Wu, S. Kwak
{"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":null,"pages":null},"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}
引用次数: 0
The Dai–Liao-type conjugate gradient methods for solving vector optimization problems 解决矢量优化问题的戴-里奥型共轭梯度法
IF 2.2 3区 数学
Optimization Methods & Software Pub Date : 2024-07-23 DOI: 10.1080/10556788.2024.2380697
Bo-Ya Zhang, Qing-Rui He, Chun-Rong Chen, Sheng-Jie Li, Ming-Hua Li
{"title":"The Dai–Liao-type conjugate gradient methods for solving vector optimization problems","authors":"Bo-Ya Zhang, Qing-Rui He, Chun-Rong Chen, Sheng-Jie Li, Ming-Hua Li","doi":"10.1080/10556788.2024.2380697","DOIUrl":"https://doi.org/10.1080/10556788.2024.2380697","url":null,"abstract":"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...","PeriodicalId":54673,"journal":{"name":"Optimization Methods & Software","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141944251","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}
引用次数: 0
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