On the Learning Behavior of Adaptive Networks - Part II: Performance Analysis
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This work deals with the topic of information processing over graphs. The presentation is largely self-contained and covers results that relate to the analysis and design of multi-agent networks for the distributed solution of optimization, adaptation, and ...
We propose an algorithm to learn from distributed data on a network of arbitrarily connected machines without exchange of the data-points. Parts of the dataset are processed locally at each machine, and then the consensus communication algorithm is employe ...
This work characterizes the nature of the limit point of distributed strategies for adaptation and learning over networks in the general case when the combination policy is not necessarily doubly stochastic and when the individual risks do not necessarily ...
Adaptive networks are well-suited to perform decentralized information processing and optimization tasks and to model various types of self-organized and complex behavior encountered in nature. Adaptive networks consist of a collection of agents with proce ...
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 ...
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This work shows how the combination weights of diffusion strategies for adaptation and learning over networks can be chosen in order for the network mean-square-error performance to match that of an optimized centralized (or batch) solution. The results sh ...
In this work, we analyze the generalization ability of distributed online learning algorithms under stationary and non-stationary environments. We derive bounds for the excess-risk attained by each node in a connected network of learners and study the perf ...
Nature provides splendid examples of real-time learning and adaptation behavior that emerges from highly localized interactions among agents of limited capabilities. For example, schools of fish are remarkably apt at configuring their topologies almost ins ...
Abstract—This paper presents a method for plug-and-play distributed MPC of a network of interacting linear systems. The previously introduced idea of plug and play control addresses the challenge of performing network changes in the form of subsystems that ...
This paper presents a method for plug-and-play distributed MPC of a network of interacting linear systems. The previously introduced idea of plug and play control addresses the challenge of performing network changes in the form of subsystems that are join ...