您的检索：
学者姓名：张海斌
精炼检索结果：
年份
成果类型
收录类型
来源
综合
合作者
语言
清除所有精炼条件
摘要 ：
In an era of data explosion and uncertain information, online optimization becomes a more and more powerful framework. And online DR-submodular maximization is an important subclass because its wide aplications in machine learning, statistics, etc., and significance for exploring general non-convex problems. In this paper, we focus on the online non-monotone DR-submodular maximizaition under general constraint set, and propose a meta-Frank-Wolfe online algorithm with appropriately choosing parameters. Based on the Lyapunov function approach in [8] and variance reduction technique in [16], we show that the proposed online algorithm attains sublinear regret against a 1/4 approximation ratio to the best fixed action in hindsight.
关键词 ：
Variance reduction Variance reduction Regret Regret Approximation ratio Approximation ratio Online optimization Online optimization DR-submodularity DR-submodularity
引用：
复制并粘贴一种已设定好的引用格式，或利用其中一个链接导入到文献管理软件中。
| GB/T 7714 | Feng, Junkai , Yang, Ruiqi , Zhang, Haibin et al. Online Non-monotone DR-Submodular Maximization: 1/4 Approximation Ratio and Sublinear Regret [J]. | COMPUTING AND COMBINATORICS, COCOON 2022 , 2022 , 13595 : 118-125 . |
| MLA | Feng, Junkai et al. "Online Non-monotone DR-Submodular Maximization: 1/4 Approximation Ratio and Sublinear Regret" . | COMPUTING AND COMBINATORICS, COCOON 2022 13595 (2022) : 118-125 . |
| APA | Feng, Junkai , Yang, Ruiqi , Zhang, Haibin , Zhang, Zhenning . Online Non-monotone DR-Submodular Maximization: 1/4 Approximation Ratio and Sublinear Regret . | COMPUTING AND COMBINATORICS, COCOON 2022 , 2022 , 13595 , 118-125 . |
| 导入链接 | NoteExpress RIS BibTex |
引用：
复制并粘贴一种已设定好的引用格式，或利用其中一个链接导入到文献管理软件中。
| GB/T 7714 | Bai, Bofeng , Zhang, Haibin , Cheng, Lixin et al. Selected Papers from the 1st International Symposium on Thermal-Fluid Dynamics (ISTFD2019) [J]. | HEAT TRANSFER ENGINEERING , 2021 . |
| MLA | Bai, Bofeng et al. "Selected Papers from the 1st International Symposium on Thermal-Fluid Dynamics (ISTFD2019)" . | HEAT TRANSFER ENGINEERING (2021) . |
| APA | Bai, Bofeng , Zhang, Haibin , Cheng, Lixin , Ghajar, Afshin J. . Selected Papers from the 1st International Symposium on Thermal-Fluid Dynamics (ISTFD2019) . | HEAT TRANSFER ENGINEERING , 2021 . |
| 导入链接 | NoteExpress RIS BibTex |
摘要 ：
Privacy-preserving empirical risk minimization model is crucial for the increasingly frequent setting of analyzing personal data, such as medical records, financial records, etc. Due to its advantage of a rigorous mathematical definition, differential privacy has been widely used in privacy protection and has received much attention in recent years of privacy protection. With the advantages of iterative algorithms in solving a variety of problems, like empirical risk minimization, there have been various works in the literature that target differentially private iteration algorithms, especially the adaptive iterative algorithm. However, the solution of the final model parameters is imprecise because of the vast privacy budget spending on the step size search. In this paper, we first proposed a novel adaptive differential privacy algorithm that does not require the privacy budget for step size determination. Then, through the theoretical analyses, we prove that our proposed algorithm satisfies differential privacy, and their solutions achieve sufficient accuracy by infinite steps. Furthermore, numerical analysis is performed based on real-world databases. The results indicate that our proposed algorithm outperforms existing algorithms for model fitting in terms of accuracy.
关键词 ：
Differential privacy Differential privacy empirical risk minimization empirical risk minimization iteration algorithm iteration algorithm
引用：
复制并粘贴一种已设定好的引用格式，或利用其中一个链接导入到文献管理软件中。
| GB/T 7714 | Zhang, Kaili , Zhang, Haibin , Zhao, Pengfei et al. A Novel Adaptive Differential Privacy Algorithm for Empirical Risk Minimization [J]. | ASIA-PACIFIC JOURNAL OF OPERATIONAL RESEARCH , 2021 , 38 (05) . |
| MLA | Zhang, Kaili et al. "A Novel Adaptive Differential Privacy Algorithm for Empirical Risk Minimization" . | ASIA-PACIFIC JOURNAL OF OPERATIONAL RESEARCH 38 . 05 (2021) . |
| APA | Zhang, Kaili , Zhang, Haibin , Zhao, Pengfei , Chen, Haibin . A Novel Adaptive Differential Privacy Algorithm for Empirical Risk Minimization . | ASIA-PACIFIC JOURNAL OF OPERATIONAL RESEARCH , 2021 , 38 (05) . |
| 导入链接 | NoteExpress RIS BibTex |
摘要 ：
In the fields of wireless communication and data processing, there are varieties of mathematical optimization problems, especially nonconvex and nonsmooth problems. For these problems, one of the biggest difficulties is how to improve the speed of solution. To this end, here we mainly focused on a minimization optimization model that is nonconvex and nonsmooth. Firstly, an inertial Douglas-Rachford splitting (IDRS) algorithm was established, which incorporate the inertial technology into the framework of the Douglas-Rachford splitting algorithm. Then, we illustrated the iteration sequence generated by the proposed IDRS algorithm converges to a stationary point of the nonconvex nonsmooth optimization problem with the aid of the Kurdyka-Lojasiewicz property. Finally, a series of numerical experiments were carried out to prove the effectiveness of our proposed algorithm from the perspective of signal recovery. The results are implicit that the proposed IDRS algorithm outperforms another algorithm.
关键词 ：
nonconvex and nonsmooth optimization nonconvex and nonsmooth optimization Kurdyka-Lojasiewicz property Kurdyka-Lojasiewicz property Douglas-Rachford splitting Douglas-Rachford splitting inertial inertial
引用：
复制并粘贴一种已设定好的引用格式，或利用其中一个链接导入到文献管理软件中。
| GB/T 7714 | Feng, Junkai , Zhang, Haibin , Zhang, Kaili et al. An inertial Douglas-Rachford splitting algorithm for nonconvex and nonsmooth problems [J]. | CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE , 2021 , 35 (17) . |
| MLA | Feng, Junkai et al. "An inertial Douglas-Rachford splitting algorithm for nonconvex and nonsmooth problems" . | CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE 35 . 17 (2021) . |
| APA | Feng, Junkai , Zhang, Haibin , Zhang, Kaili , Zhao, Pengfei . An inertial Douglas-Rachford splitting algorithm for nonconvex and nonsmooth problems . | CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE , 2021 , 35 (17) . |
| 导入链接 | NoteExpress RIS BibTex |
引用：
复制并粘贴一种已设定好的引用格式，或利用其中一个链接导入到文献管理软件中。
| GB/T 7714 | Zhang, Yuqi , Zhang, Haibin , Tian, Yingjie . Sparse multiple instance learning with non -convex penalty [J]. | NEUROCOMPUTING , 2020 , 391 : 142-156 . |
| MLA | Zhang, Yuqi et al. "Sparse multiple instance learning with non -convex penalty" . | NEUROCOMPUTING 391 (2020) : 142-156 . |
| APA | Zhang, Yuqi , Zhang, Haibin , Tian, Yingjie . Sparse multiple instance learning with non -convex penalty . | NEUROCOMPUTING , 2020 , 391 , 142-156 . |
| 导入链接 | NoteExpress RIS BibTex |
摘要 ：
In this paper, we propose a hybrid Bregman alternating direction method of multipliers for solving the linearly constrained difference-of-convex problems whose objective can be written as the sum of a smooth convex function with Lipschitz gradient, a proper closed convex function and a continuous concave function. At each iteration, we choose either subgradient step or proximal step to evaluate the concave part. Moreover, the extrapolation technique was utilized to compute the nonsmooth convex part. We prove that the sequence generated by the proposed method converges to a critical point of the considered problem under the assumption that the potential function is a Kurdyka-Lojasiewicz function. One notable advantage of the proposed method is that the convergence can be guaranteed without the Lischitz continuity of the gradient function of concave part. Preliminary numerical experiments show the efficiency of the proposed method.
关键词 ：
Alternating direction method of multipliers Alternating direction method of multipliers Kurdyka-Lojasiewicz function Kurdyka-Lojasiewicz function Linearly constrained difference-of-convex problems Linearly constrained difference-of-convex problems Bregman distance Bregman distance
引用：
复制并粘贴一种已设定好的引用格式，或利用其中一个链接导入到文献管理软件中。
| GB/T 7714 | Tu, Kai , Zhang, Haibin , Gao, Huan et al. A hybrid Bregman alternating direction method of multipliers for the linearly constrained difference-of-convex problems [J]. | JOURNAL OF GLOBAL OPTIMIZATION , 2020 , 76 (4) : 665-693 . |
| MLA | Tu, Kai et al. "A hybrid Bregman alternating direction method of multipliers for the linearly constrained difference-of-convex problems" . | JOURNAL OF GLOBAL OPTIMIZATION 76 . 4 (2020) : 665-693 . |
| APA | Tu, Kai , Zhang, Haibin , Gao, Huan , Feng, Junkai . A hybrid Bregman alternating direction method of multipliers for the linearly constrained difference-of-convex problems . | JOURNAL OF GLOBAL OPTIMIZATION , 2020 , 76 (4) , 665-693 . |
| 导入链接 | NoteExpress RIS BibTex |
摘要 ：
Nonlinear conjugate gradient methods are among the most preferable and effortless methods to solve smooth optimization problems. Due to their clarity and low memory requirements, they are more desirable for solving large-scale smooth problems. Conjugate gradient methods make use of gradient and the previous direction information to determine the next search direction, and they require no numerical linear algebra. However, the utility of nonlinear conjugate gradient methods has not been widely employed in solving nonsmooth optimization problems. In this paper, a modified nonlinear conjugate gradient method, which achieves the global convergence property and numerical efficiency, is proposed to solve large-scale nonsmooth convex problems. The new method owns the search direction, which generates sufficient descent property and belongs to a trust region. Under some suitable conditions, the global convergence of the proposed algorithm is analyzed for nonsmooth convex problems. The numerical efficiency of the proposed algorithm is tested and compared with some existing methods on some large-scale nonsmooth academic test problems. The numerical results show that the new algorithm has a very good performance in solving large-scale nonsmooth problems.
关键词 ：
Conjugate gradient method Conjugate gradient method Global convergence Global convergence Moreau-Yosida regularization Moreau-Yosida regularization Nonsmooth large-scale problems Nonsmooth large-scale problems
引用：
复制并粘贴一种已设定好的引用格式，或利用其中一个链接导入到文献管理软件中。
| GB/T 7714 | Woldu, Tsegay Giday , Zhang, Haibin , Zhang, Xin et al. A Modified Nonlinear Conjugate Gradient Algorithm for Large-Scale Nonsmooth Convex Optimization [J]. | JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS , 2020 , 185 (1) : 223-238 . |
| MLA | Woldu, Tsegay Giday et al. "A Modified Nonlinear Conjugate Gradient Algorithm for Large-Scale Nonsmooth Convex Optimization" . | JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS 185 . 1 (2020) : 223-238 . |
| APA | Woldu, Tsegay Giday , Zhang, Haibin , Zhang, Xin , Fissuh, Yemane Hailu . A Modified Nonlinear Conjugate Gradient Algorithm for Large-Scale Nonsmooth Convex Optimization . | JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS , 2020 , 185 (1) , 223-238 . |
| 导入链接 | NoteExpress RIS BibTex |
摘要 ：
This work analyzes the alternating minimization (AM) method for solving double sparsity constrained minimization problem, where the decision variable vector is split into two blocks. The objective function is a separable smooth function in terms of the two blocks. We analyze the convergence of the method for the non-convex objective function and prove a rate of convergence of the norms of the partial gradient mappings. Then, we establish a non-asymptotic sub-linear rate of convergence under the assumption of convexity and the Lipschitz continuity of the gradient of the objective function. To solve the sub-problems of the AM method, we adopt the so-called iterative thresholding method and study their analytical properties. Finally, some future works are discussed.
关键词 ：
convergence rate convergence rate double sparsity constrained problem double sparsity constrained problem Alternating minimization Alternating minimization partial gradient mappings partial gradient mappings smooth function smooth function
引用：
复制并粘贴一种已设定好的引用格式，或利用其中一个链接导入到文献管理软件中。
| GB/T 7714 | Gao, Huan , Li, Yingyi , Zhang, Haibin . The Analysis of Alternating Minimization Method for Double Sparsity Constrained Optimization Problem [J]. | ASIA-PACIFIC JOURNAL OF OPERATIONAL RESEARCH , 2020 , 37 (4) . |
| MLA | Gao, Huan et al. "The Analysis of Alternating Minimization Method for Double Sparsity Constrained Optimization Problem" . | ASIA-PACIFIC JOURNAL OF OPERATIONAL RESEARCH 37 . 4 (2020) . |
| APA | Gao, Huan , Li, Yingyi , Zhang, Haibin . The Analysis of Alternating Minimization Method for Double Sparsity Constrained Optimization Problem . | ASIA-PACIFIC JOURNAL OF OPERATIONAL RESEARCH , 2020 , 37 (4) . |
| 导入链接 | NoteExpress RIS BibTex |
摘要 ：
A positive-definite homogeneous multivariate form plays a critical role in the medical imaging and automatic control, and the definiteness of this form can be identified by a special structure tensor. In this paper, we first state the equivalence between the positive-definite multivariate form and the corresponding tensor and account for the links between the positive-definite tensor with a strong H-tensor. Then based on weak reducibility, some criteria were provided to identify strong H-tensors. Furthermore, with these relations, we establish an iterative scheme to identify the positive-definite multivariate homogeneous form and prove it is theoretically valid. Numerical experiments were given to illustrate the practicality of the scheme.
关键词 ：
homogeneous multivariate form homogeneous multivariate form iterative scheme iterative scheme Positive definiteness Positive definiteness strong H-tensor strong H-tensor weakly reducible weakly reducible
引用：
复制并粘贴一种已设定好的引用格式，或利用其中一个链接导入到文献管理软件中。
| GB/T 7714 | Zhang, Kaili , Zhang, Haibin , Zhao, Pengfei et al. An iterative scheme for testing the positive definiteness of multivariate homogeneous forms* [J]. | INTERNATIONAL JOURNAL OF COMPUTER MATHEMATICS , 2019 , 96 (12) : 2461-2472 . |
| MLA | Zhang, Kaili et al. "An iterative scheme for testing the positive definiteness of multivariate homogeneous forms*" . | INTERNATIONAL JOURNAL OF COMPUTER MATHEMATICS 96 . 12 (2019) : 2461-2472 . |
| APA | Zhang, Kaili , Zhang, Haibin , Zhao, Pengfei , Wang, Xueyong . An iterative scheme for testing the positive definiteness of multivariate homogeneous forms* . | INTERNATIONAL JOURNAL OF COMPUTER MATHEMATICS , 2019 , 96 (12) , 2461-2472 . |
| 导入链接 | NoteExpress RIS BibTex |
摘要 ：
Recently, some proximal-based alternating direction methods and alternating projection-based prediction-correction methods were proposed to solve the structured variational inequalities in Euclidean space . We note that the proximal-based alternating direction methods need to solve its subproblems exactly. However, the subproblems of the proximal-based alternating direction methods are too difficult to be solved exactly in many practical applications. We also note that the existing alternating projection based prediction-correction methods just can cope with the case that the underlying mappings are Lipschitz continuous. However, it could be difficult to verify their Lipschitz continuity condition, provided that the available information is only the mapping values. In this paper, we present a new alternating projection-based prediction-correction method for solving the structured variational inequalities, where the underlying mappings are continuous. In each iteration, we first employ a new Armijo linesearch to derive the predictors, and then update the next iterate via some minor computations. Under some mild assumptions, we establish the global convergence theorem of the proposed method. Preliminary numerical results are also reported to illustrate the effectiveness of the proposed method.
关键词 ：
continuous mappings continuous mappings Structured variational inequalities Structured variational inequalities prediction-correction method prediction-correction method alternating projection alternating projection Armijo linesearch Armijo linesearch global convergence global convergence
引用：
复制并粘贴一种已设定好的引用格式，或利用其中一个链接导入到文献管理软件中。
| GB/T 7714 | Tu, K. , Zhang, H. B. , Xia, F. Q. . A new alternating projection-based prediction-correction method for structured variational inequalities [J]. | OPTIMIZATION METHODS & SOFTWARE , 2019 , 34 (4) : 707-730 . |
| MLA | Tu, K. et al. "A new alternating projection-based prediction-correction method for structured variational inequalities" . | OPTIMIZATION METHODS & SOFTWARE 34 . 4 (2019) : 707-730 . |
| APA | Tu, K. , Zhang, H. B. , Xia, F. Q. . A new alternating projection-based prediction-correction method for structured variational inequalities . | OPTIMIZATION METHODS & SOFTWARE , 2019 , 34 (4) , 707-730 . |
| 导入链接 | NoteExpress RIS BibTex |
导出
| 数据： |
选中 到 |
| 格式： |
