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Complex networks: Structure and dynamics

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The major concepts and results recently achieved in the study of the structure and dynamics of complex networks are reviewed, and the relevant applications of these ideas in many different disciplines are summarized, ranging from nonlinear science to biology, from statistical mechanics to medicine and engineering.
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This article is published in Physics Reports.The article was published on 2006-02-01 and is currently open access. It has received 9441 citations till now. The article focuses on the topics: Network dynamics & Complex network.

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Reconstructing propagation networks with natural diversity and identifying hidden sources.

TL;DR: A framework based on compressed sensing is developed to reconstruct complex networks on which stochastic spreading dynamics take place, finding that a full reconstruction of inhomogeneous interactions can be achieved from small amounts of polarized (binary) data, a virtue of compressed sensing.
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Approaching human language with complex networks.

TL;DR: It is shown that the models and quantitative tools of complex networks can constitute an operational methodology for linguistic inquiry, which contributes to the understanding of human language and the development of linguistics.
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Weighted Multiplex Networks

TL;DR: A theoretical framework based on the entropy of multiplex ensembles is introduced to quantify the information stored in multiplex networks that would remain undetected if the single layers were analyzed in isolation.
Posted Content

On the effect of spatial structure on the evolution of cooperation

TL;DR: A systematic and exhaustive simulation in the different degrees of freedom of the problem shows the robustness of the effect of spatial structure against changes in the update rule, and refute what seems to be established opinions in the field.
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Optimization by Simulated Annealing

TL;DR: There is a deep and useful connection between statistical mechanics and multivariate or combinatorial optimization (finding the minimum of a given function depending on many parameters), and a detailed analogy with annealing in solids provides a framework for optimization of very large and complex systems.
Book

Computers and Intractability: A Guide to the Theory of NP-Completeness

TL;DR: The second edition of a quarterly column as discussed by the authors provides a continuing update to the list of problems (NP-complete and harder) presented by M. R. Garey and myself in our book "Computers and Intractability: A Guide to the Theory of NP-Completeness,” W. H. Freeman & Co., San Francisco, 1979.
Journal ArticleDOI

Collective dynamics of small-world networks

TL;DR: Simple models of networks that can be tuned through this middle ground: regular networks ‘rewired’ to introduce increasing amounts of disorder are explored, finding that these systems can be highly clustered, like regular lattices, yet have small characteristic path lengths, like random graphs.
Book

Matrix computations

Gene H. Golub
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The authors review the major concepts and results recently achieved in the study of the structure and dynamics of complex networks, and summarize the relevant applications of these ideas in many different disciplines, ranging from nonlinear science to biology, from statistical mechanics to medicine and engineering.