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.

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...

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...

Various evolving approaches have been extensively applied to evolve densely connected communities in complex networks. However these techniques have been primarily single objective optimization techniques, which optimize only a specific feature of the network missing on other important features....

In the last decade, the problem of community detection in complex networks has attracted the attention of many researchers in many domains, several methods and algorithms have been proposed to deal with this problem, many of them consider it as an optimization problem and various bio-inspired...

This article describes how parallel to the continuous growth of the Internet, which allows people to share and collaborate more, social networks have become more attractive as a research topic in many different disciplines. Community structures are established upon interactions between people....

Complex networks methodology has permeated the spheres of knowledge that deal with heterogeneous networks, introduced by Actor-Network Theory. In the context, cognition of macro socio-economic processes that have determinants, different in ontological sense, does not seem to be so efficient. The...

Libre Software communities are among the most interesting and advanced socio-economic laboratories on the Net. In terms of directions of Regional Science research, this paper addresses a simple question: “Is the socio-economics of digital nets out of scope for Regional Science, or might the...

This paper investigates how economic shocks propagate and amplify through the input-output network connecting industrial sectors in developed economies. We study alternative models of diffusion on networks and we calibrate them using input-output data on real-world inter-sectoral dependencies...

In this paper we apply agent-based methodology on an issue that is fundamental for economic prosperity and growth: the diffusion of innovations. The diffusion of innovations is one of the topics where agent-based simulation is an extremely fruitful method allowing not only the observation of...