Randomized incremental protocols over adaptive networks
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The MEU GIS-enabled web-platform [1] has been developed in close collaboration with four Swiss cities. The tool enables detailed monitoring and planning for both energy demand and supply at individual building, neighborhood and whole city scale (http://meu ...
In this work and the supporting Parts II and III of this paper, also in the current issue, we provide a rather detailed analysis of the stability and performance of asynchronous strategies for solving distributed optimization and adaptation problems over n ...
Institute of Electrical and Electronics Engineers2015
Realistic simulation of tool-tissue interactions can help to develop more effective surgical training systems and simulators. This study uses a finite element and meshless modeling approach to simulate the grasping procedure of a large intra-abdominal orga ...
There has been a recent surge in methods targeting the recovery of a speed-of-sound map from pulse-echo ultrasound measurements. We focused in this work on a particular technique and identified a drawback shared by similar methods - namely the necessity of ...
Simulation-based optimization models are widely applied to find optimal operating conditions of processes. Often, computational challenges arise from model complexity, making the generation of reliable design solutions difficult. We propose an algorithm fo ...
Ensuring correct network behavior is hard. This is the case even for simple networks, and adding middleboxes only complicates this task. In this paper, we demonstrate a fundamental property of networks. Namely, we show a way of using a network to emulate t ...
In Part I of this paper, also in this issue, we introduced a fairly general model for asynchronous events over adaptive networks including random topologies, random link failures, random data arrival times, and agents turning on and off randomly. We perfor ...
Institute of Electrical and Electronics Engineers2015
Adaptive networks consist of a collection of agents with adaptation and learning abilities. The agents interact with each other on a local level and diffuse information across the network through their collaboration. In this work, we consider two types of ...
Institute of Electrical and Electronics Engineers, Inc., 345 E. 47 th St. NY NY 10017-2394 United States2013
The multitask diffusion LMS is an efficient strategy to simultaneously infer, in a collaborative manner, multiple parameter vectors. Existing works on multitask problems assume that all agents respond to data synchronously. In several applications, agents ...
Over recent years, many large network datasets become available, giving rise to novel and valuable applications of data mining and machine learning techniques. These datasets include social networks, the structure of the Internet, and protein-interaction n ...