Many systems can be described using graphs, or networks. Detecting communities in these networks can provide information about the underlying structure and functioning of the original systems. Yet this detection is a complex task and a large amount of work was dedicated to it in the past decade. One important feature is that communities can be found at several scales, or levels of resolution, i...

Many real-world networks have a common feature of organization, i.e., community structure. Detecting this structure is fundamental for uncovering the links between the structure and the function in complex networks and for practical applications in many disciplines such as biology and sociology. In this paper we propose a weighted parsimony criterion for community detection in complex networks....

In this work, the local optimality of mixed reliability networks is surveyed. A comparison criterion related with subgraphs to measure established. Using criterion, we characterize all locally optimally reliable among n-vertex fixed sizes m=n, m=n+1 and m=n+2, respectively.

The recently introduced dropout training criterion for neural networks has been the subject of much attention due to its simplicity and remarkable effectiveness as a regularizer, as well as its interpretation as a training procedure for an exponentially large ensemble of networks that share parameters. In this work we empirically investigate several questions related to the efficacy of dropout,...

This doctoral dissertation introduces an algorithm for constructing the most probable Bayesian network from data for small domains. The algorithm is used to show that a popular goodness criterion for the Bayesian networks has a severe sensitivity problem. The dissertation then proposes an information theoretic criterion that avoids the problem. Computing Reviews (1998)

This paper presents a stability criterion for global asymptotic stability of the equilibrium point for Bidirectional Associative Memory (BAM) neural networks with fixed time delays. An approach combining the Lyapunov-Krasovskii functional with Linear Matrix Inequality (LMI) is taken to investigate the stability of the system. A delay-dependent LMI criterion is derived. Finally, a numerical exam...

The shapes that networks form are thought to be related to the performance of networks during this process. Using reduced travel time as an evaluation criterion, this study examines growth of road and rail transportation networks to determine the differences in growth patterns that are caused by various factors, including speed on transportation network.

The most common fitness evaluation for Bayesian networks in the presence of data is the Cooper-Herskovitz criterion. This technique involves massive amounts of data and, therefore, expansive computations. We propose a cheaper alternative evaluation method using simplified assumptions which produces evaluations that are strongly correlated with the Cooper-Herskovitz criterion .

Memristive neural networks are a novel topic in the design and construction of brain-like circuitry system. This paper addresses a challenging problem: How to derive some less conservative theoretical results on the stability and attractability for memristive neural networks? In this paper, a new comparison method and segmentation method of state space are developed. A succinct criterion is pro...

A hybrid mobile communication network as considered in this paper consists of a point-to-point network (UMTS) and a point-to-multipoint network (DVB-H). The benefit of combining these two networks is an optimised transfer of data by collecting several user requests for a single response via the broadcast network. Thus, capacity can be saved, UMTS cells can be unloaded and the mean response time...