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Small-world networks embedded in Euclidean space represent useful cartoon models for a number of real systems such as electronic circuits, communication systems, the large-scale brain architecture and others. Since the small-world behavior relies on the pr ...
The application of decentralized reputation systems is a promising approach to ensure cooperation and fairness, as well as to address random failures and malicious attacks in Mobile Ad-Hoc Networks. However, they are potentially vulnerable to liars. With o ...
Distributed co-ordination is the result of dynamical processes enabling independent agents to coordinate their actions without the need of a central co-ordinator. In the past few years, several computational models have illustrated the role played by such ...
A longstanding problem in the study of sediment transport in gravel-bed rivers is related to the physical mechanisms governing bed resistance and particle motion. To study this problem, we investigated the motion of coarse spherical glass beads entrained b ...
In this paper, we study the problem of content-based social network discovery among people who frequently appear in world news. Google news is used as the source of data. We describe a probabilistic framework for associating people with groups. A low-dimen ...
Modellers are increasingly relying on the use of continuous random coefficients models, such as Mixed Logit, for the representation of variations in tastes across individuals. In this paper, we provide an in-depth comparison of the performance of the Mixed ...
We present a general method for maintaining estimates of the distribution of parameters in arbitrary models. This is then applied to the estimation of probability distributions over actions in value-based reinforcement learning. While this approach is simi ...
This paper presents a validation study on statistical non-supervised brain tissue classification techniques in MR images. Several image models assuming different hypotheses regarding the intensity distribution model, the spatial model and the number of cla ...
Energy-based detection and estimation are crucial in sensor networks for sensor localization, target tracking, etc. In this paper, we present novel Gaussian approximations that are applicable to general energy-based source detection and localization proble ...
Periodic cellular configurations with negative Poisson's ratio have attracted the attention of several researchers because of their superior dynamic characteristics. Among the geometries with a negative Poisson's ratio, the chiral topology features localiz ...