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Decentralized clustering over adaptive networks

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Fitness of Business Models for Digital Collaborative Platforms in Clusters: A Case Study

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This paper investigates the role of business models for exploiting digital options within digital clusters (that are clusters where collaboration is IT-dependent). To this aim, this research focuses on digital platforms, a specific IT artifact supporting a ...

Springer International Publishing2015

Particle clustering phenomena in hot asphalt mixtures with high content of reclaimed asphalt pavements

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Elsevier Sci Ltd2015

Distributed Clustering and Learning Over Networks

Ali H. Sayed

Distributed processing over networks relies on in-network processing and cooperation among neighboring agents. Cooperation is beneficial when agents share a common objective. However, in many applications, agents may belong to different clusters that pursu ...

IEEE2015

A Novel Technique for Online Partial Discharge Pattern Recognition in Large Electrical Motors

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In this paper, a fully automated system for source detection of the partial discharges (PD) as an online diagnosis test in rotating machineries is proposed. This technique uses a modified version of the Expectation Maximization-based (EM) clustering techni ...

Ieee2014

Quasar: Resource-Efficient and QoS-Aware Cluster Management

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Cloud computing promises flexibility and high performance for users and high cost-efficiency for operators. Nevertheless, most cloud facilities operate at very low utilization, hurting both cost effectiveness and future scalability. We present Quasar, a cl ...

2014

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The organization of connectivity in neuronal networks is fundamental to understanding the activity and function of neural networks and information processing in the brain. Recent studies show that the neocortex is not only organized in columns and layers b ...

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Cluster formation over adaptive networks with selfish agents

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We examine the problem of adaptation and learning over networks with selfish agents. In order to motivate agents to cooperate, we allow the agents to select their partners according to whether they can help them reduce their utility costs. We divide the op ...

2013

Cooperative off-policy prediction of Markov decision processes in adaptive networks

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We apply diffusion strategies to propose a cooperative reinforcement learning algorithm, in which agents in a network communicate with their neighbors to improve predictions about their environment. The algorithm is suitable to learn off-policy even in lar ...

IEEE2013

Implementation of a Distributed Computation Framework

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This project aims at building a dynamic and scalable framework for Byzantine fault tolerant distributed computation. By organizing nodes of a distributed system in fault-tolerant clusters, we mask Byzantine failures of single nodes and provide an abstracti ...

2013

Clustering via diffusion adaptation over networks

Ali H. Sayed

Distributed processing over networks relies on in-network processing and cooperation among neighboring agents. Cooperation is beneficial when all agents share the same objective or belong to the same group. However, if agents belong to different clusters o ...

IEEE2012