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Learning a Coupled Linearized Method in Online Setting | |
Xue, Wei1![]() ![]() | |
发表期刊 | IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
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2017-02-01 | |
卷号 | 28期号:2页码:438-450 |
文章类型 | Article |
摘要 | Based on the alternating direction method of multipliers, in this paper, we propose, analyze, and test a coupled linearized method, which aims to minimize an unconstrained problem consisting of a loss term and a regularization term in an online setting. To solve this problem, we first transform it into an equivalent constrained minimization problem with a separable structure. Then, we split the corresponding augmented Lagrangian function and minimize the resulting subproblems distributedly with one variable by fixing another one. This method is easy to execute without calculating matrix inversion by implementing three linearized operations per iteration, and at each iteration, we can obtain a closed-form solution. In particular, our update rule contains the well-known soft-thresholding operator as a special case. Moreover, upper bound on the regret of the proposed method is analyzed. Under some mild conditions, it can achieve 0(1/ root T) convergence rate for convex learning problems and 0((logT)/ T) for strongly convex learning. Numerical experiments and comparisons with several state-of-the-art methods are reported, which demonstrate the efficiency and effectiveness of our approach. |
关键词 | Alternating Minimization Convex Optimization Linearized Operation Online Learning Regret Bound |
WOS标题词 | Science & Technology ; Technology |
DOI | 10.1109/TNNLS.2016.2514413 |
关键词[WOS] | OPTIMIZATION METHODS ; ALGORITHM ; REGRESSION ; SHRINKAGE ; SELECTION |
收录类别 | SCI |
语种 | 英语 |
项目资助者 | National Natural Science Foundation of China(U1135005 ; Project of Post-Graduate Scientific Research Innovation Program of Jiangsu Province(KYZZ15_0123) ; 61305018 ; 61432008 ; 61472423 ; 61532006) |
WOS研究方向 | Computer Science ; Engineering |
WOS类目 | Computer Science, Artificial Intelligence ; Computer Science, Hardware & Architecture ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic |
WOS记录号 | WOS:000394522900017 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/14383 |
专题 | 多模态人工智能系统全国重点实验室_人工智能与机器学习(杨雪冰)-技术团队 |
作者单位 | 1.Nanjing Univ Sci & Technol, Sch Comp Sci & Engn, Nanjing 210094, Jiangsu, Peoples R China 2.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China |
推荐引用方式 GB/T 7714 | Xue, Wei,Zhang, Wensheng. Learning a Coupled Linearized Method in Online Setting[J]. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,2017,28(2):438-450. |
APA | Xue, Wei,&Zhang, Wensheng.(2017).Learning a Coupled Linearized Method in Online Setting.IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,28(2),438-450. |
MLA | Xue, Wei,et al."Learning a Coupled Linearized Method in Online Setting".IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 28.2(2017):438-450. |
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