We demonstrate for the case of single-layer neural networks how an extension of the TAP mean-field approach of disorder physics can be applied to the computation of approximate averages in probabilistic models for real data.

We investigate the finite size corrections to the equilibrium magnetization of an Ising model on a random graph with N nodes and Nγ edges, with 1γ≤2. By conveniently rescaling the coupling constant, the free energy is made extensive. As expected, the system displays a phase transition of the...

To describe the dynamics of learning an input–output relation from a set of examples, the evolution of an appropriate choice of macroscopic dynamical variables have to be found. Recent progress in on-line learning only addresses the often unrealistic case of an infinite training set. For...

In this paper, we propose a novel node importance evaluation method from the perspective of the existence of mutual dependence among nodes. The node importance comprises its initial importance and the importance contributions from both the adjacent and non-adjacent nodes according to the...

Functional networks, i.e. networks representing dynamic relationships between the components of a complex system, have been instrumental for our understanding of, among others, the human brain. Due to limited data availability, the multi-layer nature of numerous functional networks has hitherto...

We study the topological properties of the information transfer networks (ITN) of the global financial market indices for six different periods. ITN is a directed weighted network, in which the direction and weight are determined by the transfer entropy between market indices. By applying the...

Recent studies of rumor or information diffusion process in complex networks show that in contrast to traditional comprehension, individuals who participate in rumor spreading within one network do not always get the rumor from their neighbors. They can obtain the rumor from different sources...

Identifying influential nodes in complex networks has attracted much attention because of its great theoretical significance and wide application. Existing methods consider the edges equally when designing identifying methods for the unweighted networks. In this paper, we propose an edge...

The communication infrastructure is a critical component of a large-scale cloud data center. It needs to provide the best performance available while keeping overprovisioning and, lately even more important, power consumption, to the minimum. Aiming to provide a unified solution that will have...

Many real-world networks exhibit community structure where vertices belong to one or more communities. Recent studies show that community structure plays an import role in epidemic spreading. In this paper, we investigate how the extent of overlap among communities affects epidemics. In order to...