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题名: Combined local search strategy for learning in networks of binary synapses
作者: Huang, HP ;  Zhou, HJ
刊名: EPL
出版日期: 2011
卷号: 96, 期号:5, 页码:58003
关键词: PERCEPTRON PROBLEM ;  MEMORY ;  RULES
学科分类: Physics
通讯作者: Huang, HP (reprint author), Chinese Acad Sci, Key Lab Frontiers Theoret Phys, Inst Theoret Phys, Beijing 100190, Peoples R China.
部门归属: [Huang, Haiping; Zhou, Haijun] Chinese Acad Sci, Key Lab Frontiers Theoret Phys, Inst Theoret Phys, Beijing 100190, Peoples R China; [Zhou, Haijun] Chinese Acad Sci, Kavli Inst Theoret Phys China, Inst Theoret Phys, Beijing 100190, Peoples R China; [Huang, Haiping] Hong Kong Univ Sci & Technol, Dept Phys, Hong Kong, Hong Kong, Peoples R China
英文摘要: Learning in networks of binary synapses is known to be an NP-complete problem. A combined stochastic local search strategy in the synaptic weight space is constructed to further improve the learning performance of a single random walker. We apply two correlated random walkers guided by their Hamming distance and associated energy costs (the number of unlearned patterns) to learn a same large set of patterns. Each walker first learns a small part of the whole pattern set (partially different for both walkers but with the same amount of patterns) and then both walkers explore their respective weight spaces cooperatively to find a solution to classify the whole pattern set correctly. The desired solutions locate at the common parts of weight spaces explored by these two walkers. The efficiency of this combined strategy is supported by our extensive numerical simulations and the typical Hamming distance as well as energy cost is estimated by an annealed computation. Copyright (C) EPLA, 2011
资助者: NSFC [10834014]; 973-Program [2007CB935903, HKUST 605010]
收录类别: SCI
原文出处: 查看原文
语种: 英语
WOS记录号: WOS:000298131900043
Citation statistics: 
内容类型: 期刊论文
URI标识: http://ir.itp.ac.cn/handle/311006/14223
Appears in Collections:理论物理所2011年知识产出_期刊论文

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Recommended Citation:
Huang, HP,Zhou, HJ. Combined local search strategy for learning in networks of binary synapses[J]. EPL,2011,96(5):58003.
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