Proceedings ArticleDOI
Adaptive decision-making over complex networks
Sheng-Yuan Tu,Ali H. Sayed +1 more
- pp 525-530
TLDR
This work develops and study a procedure by which the entire network can be made to follow one objective or the other through a distributed and collaborative decision process.Abstract:
It is common for biological networks to encounter situations where agents need to decide between multiple options, such as deciding between moving towards one food source or another or between moving towards a new hive or another. In previous works, we developed several powerful diffusion strategies that allow agents to estimate a model of interest in an adaptive and distributed manner through a process of in-network collaboration and learning. In this work, we consider the situation in which the data observed by the agents may arise from two different distributions or models. We develop and study a procedure by which the entire network can be made to follow one objective or the other through a distributed and collaborative decision process.read more
Citations
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Journal ArticleDOI
Multitask Diffusion Adaptation Over Networks
TL;DR: This paper employs diffusion strategies to develop distributed algorithms that address multitask problems by minimizing an appropriate mean-square error criterion with l2-regularization and demonstrates how the distributed strategy can be used in several useful applications related to target localization and hyperspectral data unmixing.
Journal ArticleDOI
Estimation of Space-Time Varying Parameters Using a Diffusion LMS Algorithm
TL;DR: This analysis reveals that the proposed algorithm can overcome the difficulty in the estimation of the space-varying parameters using distributed approaches to a large extent by benefiting from the network stochastic matrices that are used to combine exchanged information between nodes.
Proceedings ArticleDOI
Diffusion LMS for multitask problems with overlapping hypothesis subspaces
TL;DR: This paper forms an online multitask learning problem where node hypothesis spaces partly overlap, and a cooperative algorithm based on diffusion adaptation is derived.
Journal ArticleDOI
Distributed Decision-Making Over Adaptive Networks
Sheng-Yuan Tu,Ali H. Sayed +1 more
TL;DR: This paper considers the situation in which the data observed by the agents may have risen from two different models, and develops a classification scheme for agents to identify the models that generated the data, and proposes a procedure by which the entire network can be made to converge towards the same model through a collaborative decision-making process.
Proceedings ArticleDOI
Diffusion LMS for clustered multitask networks
TL;DR: In this paper, the authors employ diffusion strategies to develop distributed algorithms that address clustered multi-task problems by minimizing an appropriate mean-square error criterion with 2 -regularization, and some results on the meansquare stability and convergence of the algorithm are also provided.
References
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Self-Organization in Biological Systems
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Distributed asynchronous deterministic and stochastic gradient optimization algorithms
TL;DR: A model for asynchronous distributed computation is presented and it is shown that natural asynchronous distributed versions of a large class of deterministic and stochastic gradient-like algorithms retain the desirable convergence properties of their centralized counterparts.
Proceedings ArticleDOI
Distributed Asynchronous Deterministic and Stochastic Gradient Optimization Algorithms
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Diffusion LMS Strategies for Distributed Estimation
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Journal ArticleDOI
Diffusion Least-Mean Squares Over Adaptive Networks: Formulation and Performance Analysis
Cassio G. Lopes,Ali H. Sayed +1 more
TL;DR: Closed-form expressions that describe the network performance in terms of mean-square error quantities are derived and the resulting algorithm is distributed, cooperative and able to respond in real time to changes in the environment.
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