The soaring location-based social services not only make it possible to take advantage of one additional source of information: the places people visit, but also present graph structure consisting of individuals and places in certain relationship. In this paper we investigated the interactions between venues in Foursquare network. Provided with the check-in number for each venue as well as the ...

Due to its attributes, such as parallelism, adaptability, robustness and inherent ability to handle non-linearality, the artificial neural network has shown great promise in the function mapping, pattern recognition, imagine processing, etc. The dynamic function mapping, dynamic pattern recognition and dynamic imagine processing are still challenging topics in neural network applications. A neu...

A defining feature of many large empirical networks is their intrinsic complexity. However, many networks also contain a large degree of structural repetition. An immediate question then arises: can we characterize essential network complexity while excluding structural redundancy? In this article we utilize inherent network symmetry to collapse all redundant information from a network, resulti...

Recent studies have revealed that the Optical Transpose Interconnection Systems (OTIS) are promising candidates for future high-performance parallel computers. This paper presents and evaluates a general method for algorithm development on the OTIS-Arrangement network (OTIS-AN) as an example of OTIS network. The proposed method can be used and customized for any other OTIS network. Furthermore,...

Recent advances in the field of network embedding have shown that low-dimensional network representation is playing a critical role in network analysis. Most existing network embedding methods encode the local proximity of a node, such as the firstand secondorder proximities. While being efficient, these methods are short of leveraging the global structural information between nodes distant fro...

INTRODUCTION Several neuroimaging studies have shown that visuospatial imagery is associated with a multitude of activation nodes spanning occipital, parietal, temporal and frontal brain areas. However, the anatomical connectivity profile linking these areas is not well understood. Specifically, it is unknown whether cortical areas activated during visuospatial imagery are directly connected to...

Networks have become instrumental in deciphering how information is processed and transferred within systems in almost every scientific field today. Nearly all network analyses, however, have relied on humans to devise structural features of networks believed to be most discriminative for an application. We present a framework for comparing and classifying networks without human-crafted feature...

The use of several types of structural restrictions within algorithms for learning Bayesian networks is considered. These restrictions may codify expert knowledge in a given domain, in such a way that a Bayesian network representing this domain should satisfy them. The main goal of this paper is to study whether the algorithms for automatically learning the structure of a Bayesian network from ...

This paper uses the reliability polynomial, introduced by Moore and Shannon in 1956, to analyze the effect of network structure on diffusive dynamics such as the spread of infectious disease. We exhibit a representation for the reliability polynomial in terms of what we call structural motifs that is well suited for reasoning about the effect of a network's structural properties on diffusion ac...