INEXACT

作品数：69被引量：91H指数：4
导出分析报告
相关领域：理学更多>>
相关作者：黄记祖唐春明吕莹更多>>
相关机构：山西工程职业技术学院广西大学北京师范大学香港大学更多>>
相关期刊：《Journal of Beijing Institute of Technology》《中国多媒体与网络教学学报（电子版）》《Applied Mathematics and Mechanics(English Edition)》《World Journal of Nephrology》更多>>
相关基金：国家自然科学基金国家重点基础研究发展计划国家高技术研究发展计划中国博士后科学基金更多>>
-
在结果中检索

检索结果分析

结果分析中...
共 条 记 录，以下是1-10
全选清除导出
参考文献引证文献引用追踪
视图：
排序：
Inexact proximal gradient algorithm with random reshuffling for nonsmooth optimization
《Science China(Information Sciences)》2025年第1期216-234,共19页Xia JIANG Yanyan FANG Xianlin ZENG Jian SUN Jie CHEN 
supported in part by National Key R&D Program of China(Grant No.2021YFB1714800);National Natural Science Foundation of China(Grant Nos.61925303,62088101,62073035,62173034);Natural Science Foundation of Chongqing(Grant No.2021ZX4100027).
Proximal gradient algorithms are popularly implemented to achieve convex optimization with nonsmooth regularization.Obtaining the exact solution of the proximal operator for nonsmooth regularization is challenging bec...
关键词：proximal operator random reshuffling inexact computation compressed sensing nonsmooth optimization 
Accelerated inexact Newton-Landweber iteration method for EIT image reconstruction
《黑龙江大学自然科学学报》2024年第6期690-699,共10页YANG Xue WANG Yifan WANG Jing 
National Natural Science Foundation of China(12101204,12261021);Heilongjiang Provincial Natural Science Foundation of China(LH2023A018);Modern Numerical Method Course for Research Program on Teaching Reform of Degree and Postgraduate Education of Heilongjiang University(2024)。
The image reconstruction of electrical impedance tomography(EIT)is a nonlinear and ill-posed inverse problem and the imaging results are easily affected by measurement noise,which needs to be solved by using regulariz...
关键词：electrical impedance tomography image reconstruction Landweber iteration inexact Newton-Landweber iteration Nesterov acceleration 
AN INEXACT PROXIMAL DC ALGORITHM FOR THE LARGE-SCALE CARDINALITY CONSTRAINED MEAN-VARIANCE MODEL IN SPARSE PORTFOLIO SELECTION
《Journal of Computational Mathematics》2024年第6期1452-1501,共50页Mingcai Ding Xiaoliang Song Bo Yu 
supported by the National Natural Science Foundation of China(Grant No.11971092);supported by the Fundamental Research Funds for the Central Universities(Grant No.DUT20RC(3)079)。
Optimization problem of cardinality constrained mean-variance(CCMV)model for sparse portfolio selection is considered.To overcome the difficulties caused by cardinality constraint,an exact penalty approach is employed...
关键词：Sparse portfolio selection Cardinality constrained mean-variance model Inexact proximal difference-of-convex-functions algorithm Sieving strategy Decomposed strategy 
ADAPTIVE REGULARIZED QUASI-NEWTON METHOD USING INEXACT FIRST-ORDER INFORMATION
《Journal of Computational Mathematics》2024年第6期1656-1687,共32页Hongzheng Ruan Weihong Yang 
supported by the National Natural Science Foundation of China(Grant No.NSFC-11971118).
Classical quasi-Newton methods are widely used to solve nonlinear problems in which the first-order information is exact.In some practical problems,we can only obtain approximate values of the objective function and i...
关键词：Inexact first-order information REGULARIZATION Quasi-Newton method 
Multi-instance partial-label learning:towards exploiting dual inexact supervision被引量：1
《Science China(Information Sciences)》2024年第3期44-57,共14页Wei TANG Weijia ZHANG Min-Ling ZHANG 
supported by National Natural Science Foundation of China (Grant Nos.62225602,62206047)。
Weakly supervised machine learning algorithms are able to learn from ambiguous samples or labels,e.g.,multi-instance learning or partial-label learning.However,in some real-world tasks,each training sample is associat...
关键词：machine learning multi-instance partial-label learning multi-instance learning partial-label learning Gaussian processes 
Neural-based inexact graph de-anonymization
《High-Confidence Computing》2024年第1期52-59,共8页Guangxi Lu Kaiyang Li Xiaotong Wang Ziyue Liu Zhipeng Cai Wei Li 
supported by the National Science Foundation of U.S.(2011845,2315596 and 2244219).
Graph de-anonymization is a technique used to reveal connections between entities in anonymized graphs,which is crucial in detecting malicious activities,network analysis,social network analysis,and more.Despite its p...
关键词：Graph de-anonymization Graph convolutional network Neural tensor network 
The convergence properties of infeasible inexact proximal alternating linearized minimization被引量：1
《Science China Mathematics》2023年第10期2385-2410,共26页Yukuan Hu Xin Liu 
supported by National Natural Science Foundation of China(Grant Nos.12125108,11971466,11991021,11991020,12021001 and 12288201);Key Research Program of Frontier Sciences,Chinese Academy of Sciences(Grant No.ZDBS-LY-7022);CAS(the Chinese Academy of Sciences)AMSS(Academy of Mathematics and Systems Science)-PolyU(The Hong Kong Polytechnic University)Joint Laboratory of Applied Mathematics.
The proximal alternating linearized minimization(PALM)method suits well for solving blockstructured optimization problems,which are ubiquitous in real applications.In the cases where subproblems do not have closed-for...
关键词：proximal alternating linearized minimization INFEASIBILITY nonmonotonicity surrogate sequence inexact criterion iterate convergence asymptotic convergence rate 
Approximate Customized Proximal Point Algorithms for Separable Convex Optimization
《Journal of the Operations Research Society of China》2023年第2期383-408,共26页Hong-Mei Chen Xing-Ju Cai Ling-Ling Xu 
the National Natural Science Foundation of China(Nos.11971238 and 11871279)。
Proximal point algorithm(PPA)is a useful algorithm framework and has good convergence properties.Themain difficulty is that the subproblems usually only have iterative solutions.In this paper,we propose an inexact cus...
关键词：Inexact criteria Proximal point algorithm Alternating direction method of multipliers Separable convex programming 
Convex Reformulation for Two-sided Distributionally Robust Chance Constraints with Inexact Moment Information
《Journal of Modern Power Systems and Clean Energy》2022年第4期1060-1065,共6页Lun Yang Yinliang Xu Zheng Xu Hongbin Sun 
This work was supported by the Natural Science Foundation of Guangdong Province(No.2021A1515012450)。
Constraints on each node and line in power systems generally have upper and lower bounds,denoted as twosided constraints.Most existing power system optimization methods with the distributionally robust(DR)chance-const...
关键词：Two-sided chance constraint distributionally robust conic reformulation interval moment optimal power flow 
Limited Memory BFGS Method for Least Squares Semidefinite Programming with Banded Structure
《Journal of Systems Science & Complexity》2022年第4期1500-1519,共20页XUE Wenjuan SHEN Chungen YU Zhensheng 
supported by the National Natural Science Foundation of China under Grant No.11601318。
This work is intended to solve the least squares semidefinite program with a banded structure. A limited memory BFGS method is presented to solve this structured program of high dimension.In the algorithm, the inverse...
关键词：Banded structure inexact gradient least squares semidefinite program limited memory BFGS orthogonal iteration 
全选清除导出
共7页<1234567>
检索报告 对象比较 聚类工具 使用帮助 返回顶部