Inference of the sparse kinetic Ising model using the decimation method
Decelle, A; Zhang, P
刊名PHYSICAL REVIEW E
2015
卷号91期号:5页码:52136
通讯作者Decelle, A (reprint author), Univ Roma La Sapienza, Dipartimento Fis, Piazzale Aldo Moro 5, I-00185 Rome, Italy.
英文摘要In this paper we study the inference of the kinetic Ising model on sparse graphs by the decimation method. The decimation method, which was first proposed in Decelle and Ricci-Tersenghi [Phys. Rev. Lett. 112, 070603 (2014)] for the static inverse Ising problem, tries to recover the topology of the inferred system by setting the weakest couplings to zero iteratively. During the decimation process the likelihood function ismaximized over the remaining couplings. Unlike the l(1)-optimization-based methods, the decimation method does not use the Laplace distribution as a heuristic choice of prior to select a sparse solution. In our case, the whole process can be done automatically without fixing any parameters by hand. We show that in the dynamical inference problem, where the task is to reconstruct the couplings of an Ising model given the data, the decimation process can be applied naturally into a maximum-likelihood optimization algorithm, as opposed to the static case where pseudolikelihood method needs to be adopted. We also use extensive numerical studies to validate the accuracy of our methods in dynamical inference problems. Our results illustrate that, on various topologies and with different distribution of couplings, the decimation method outperforms the widely used l(1)-optimization-based methods.
学科主题Physics
类目[WOS]Physics, Fluids & Plasmas ; Physics, Mathematical
收录类别SCI
语种英语
内容类型期刊论文
源URL[http://ir.itp.ac.cn/handle/311006/20995]  
专题理论物理研究所_理论物理所1978-2010年知识产出
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Decelle, A,Zhang, P. Inference of the sparse kinetic Ising model using the decimation method[J]. PHYSICAL REVIEW E,2015,91(5):52136.
APA Decelle, A,&Zhang, P.(2015).Inference of the sparse kinetic Ising model using the decimation method.PHYSICAL REVIEW E,91(5),52136.
MLA Decelle, A,et al."Inference of the sparse kinetic Ising model using the decimation method".PHYSICAL REVIEW E 91.5(2015):52136.
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