The 6th International Conference on Complex Networks and Their Applications上周二到周五 11.29-12.1在法国里昂召开。与会者来自不同的领域：计算机，物理，管理，社会科学等等。给组里的同事们写了个简短的会议总结，主要是一些个人比较感兴趣的talk。这个会议中国人比较少，很多在列表上的中国学者没有到场，估计是因为签证安排经费等等问题。日本学者来的比较多。会议的论文集和摘要书可以从http://www.complexnetworks.org/  下载。

1.Argyris Kalogeratos, Kevin Scaman, Luca Corinzia and Nicolas Vayatis. Partial network immunization in Continuous-Time Information Cascades. (abstract p.113)

A new measure of node importance in spreading is defined. For each link, there is a Hazard function, representing the time-dependent infection rate, and the Hazard function is an element of the Hazard matrix. The spectral radius of the Hazard matrix is related to the size of the epidemic. Finding the Hazard matrix in a feasible set which minimizes the spectral radius is an optimization problem, and this optimized Hazard matrix denotes the best immunization strategy.

2.Jan Korbel and Xiong-Fei Jiang. Transfer entropy between communities in complex financial networks. (abstract p.240)

This work analyzes the structure of five financial markets by transfer entropy. The results show that the correlation structure and the transfer entropy structure are very different.

3.Joan T. Matamalas, Alex Arenas and Sergio Gómez. Epidemic Conductance in complex networks. (abstract p. 116)

This work studies the discrete-time SIS process via equations of states of links.

4.Xavier R. Hoffmann and Marián Boguñá. Synergistic cumulative contagion in epidemic spreading. (abstract p.118)

The work uses the Weibullian SIS process that the infection time is a Weibull renewal process. They study the memory effect of viral load by simulation. The viral load of a healthy node is accumulated by infected neighbors and will decay if there is no infected neighbor.  The infection is determined by a probability related to the viral load. The results show that the infinite memory length leads to a discontinuous phase transition of the prevalence.

5.Lluís Arola and Alex Arenas. Invariant Collective Dynamics Under Network Transformations. (abstract p.164)

This work I like a lot. They discuss the issue that the measured dynamics contain little available information of the network topology. They find a transformation of networks. A transformed network can fake the dynamics running the on original network, which means that two networks are equivalent to some extent under a same dynamical process. This work only considers the Kuramoto model.

6.Alexey Medvedev and Gabor Pete. Speeding up non-Markovian SI spreading with a few extra edges. (abstract. P.135)

This work studies non-Markovian SI process with heavy-tailed (Power-law) infection process. They find an way to accelerate the spreading by adding edges.

7.Edmund Barter and Thilo Gross. Meta-foodwebs as a many layer epidemic   process on   networks. (abstract p. 156)

The land is modeled as a network of patches which can be occupied by species. The animal diffusion is modeled by the SIS epidemic process. The species in different levels of a food chain are in corresponding different levels of the multilayer SIS process.

8.Owen Courtney and Ginestra Bianconi. Generalized network structures: The configuration model and the canonical ensemble of simplicial complexes. (abstract p. 209)

The configuration model of simplicial complexes is proposed. The simplicial complexes are a generalization of networks. The entropy of the simplicial complexes ensemble can be evaluated.

9.Ivan Kryven. Analytical expression for the size distribution of connected components in the infinite configuration model. (abstract p. 220)

The size distribution of connected components is obtained (as the title described), which is evaluated by Monte Carlo simulation.

10.Eisha Nathan, James Fairbanks and David Bader. Ranking in Dynamic Graphs using Exponential Centrality (proceeding p.378)

A new ranking metric: exponential centrality is proposed. The exponential centrality is the diagonal elements of the matrix exp(A), where A is the adjacency matrix of the network. The element exp(A)(i,i) is the related to the number of closed walks centered at node i.

11.Henk J. van Waarde, Pietro Tesi and M. Kanat Camlibel. Topology Reconstruction of Dynamical Networks via Constrained Lyapunov Equations (abstract p.187)

The linear system identification problem: given dx(t)/dt=Xx(t), x(0), estimating X, is studied. The system matrix X contains the information of the network.

12.Zhao Yang, Juan Ignacio Perotti and Claudio Juan Tessone. A comparison of hierarchical community detection algorithms (abstract p.350)

A multilevel hierarchical community network with good properties (power-law distributed degree, power-law distributed community size) and well-defined ground truth is proposed to compare the performance and efficiency of different community detection algorithm.

13.Remy Cazabet, Rim Baccour, Matthieu Latapy and Clemence Magnien. Tracking bitcoin users activity using community detection on a network of weak signals (proceeding p. 166)

The bitcoin is anonymous, but the transaction is public. This work detects the anonymous users by performing community detection on the transaction network of bitcoin.