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Complex networks exist for a number of purposes. The neural, metabolic and food networks ensure our survival, while the social, economic, transportation and communication networks allow us to prosper. Independently of the purposes and particularities of th ...
Consider a set of nodes distributed spatially over some region forming a network, where every node takes measurements of an underlying process. The objective is for every node in the network to estimate some parameter of interest from these measurements by ...
This paper addresses the problem of distributed rate allocation for a class of multicast networks employing linear network coding. The goal is to minimize the cost (for example, the sum rates allocated to each link in the network) while satisfying a multic ...
Inference from data is of key importance in many applications of informatics. The current trend in performing such a task of inference from data is to utilise machine learning algorithms. Moreover, in many applications that it is either required or is pref ...
Improved diarization results can be obtained through combination of multiple systems. Several combination techniques have been proposed based on output voting, initialization and also integrated approaches. This paper proposes and investigates a novel appr ...
This paper addresses the problem of distributed rate allocation for a class of multicast networks employing linear network coding. The goal is to minimize the cost (for example, the sum rates allocated to each link in the network) while satisfying a multic ...
It has been known for decades that the metabolic rate of animals scales with body mass with an exponent that is almost always 2/3, and often very close to 3/4. The 3/4 exponent emerges naturally from two models of resource distribution networks, radia ...
A close look at many existing systems reveals their two- or multi-layer nature, where a number of coexisting networks interact and depend on each other. For instance, in the Internet, any application-level graph (such as a peer-to-peer network) is mapped o ...
We propose a new approach for developing and deploying distributed systems, in which nodes predict distributed consequences of their actions, and use this information to detect and avoid errors. Each node continuously runs a state exploration algorithm on ...
We propose a new approach for developing and deploying distributed systems, in which nodes predict distributed consequences of their actions, and use this information to detect and avoid errors. Each node continuously runs a state exploration algorithm on ...
