Role of machine learning in configuration management of ad hoc wireless networks
Authors: 
Sung-eok Jeon, Chuanyi JiAuthors Info & Claims
Sung-eok Jeon, Chuanyi JiAuthors Info & ClaimsPages 223 - 224
Abstract
In this work, we show that machine learning, e.g., graphical models, plays an important role for the self-configuration of ad hoc wireless network. The role of such a learning approach includes a simple representation of complex dependencies in the network and a distributed algorithm which can adaptively find a nearly optimal configuration.
References
[1]
S. Geman, and D. Geman, "Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images," IEEE Trans. PAMI vol. 6, pp. 721--741, 1984
[2]
K. Huang, "Statistical Mechanics," John Wiley & Sons
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Information & Contributors
Information
Published In
August 2005
296 pages
ISBN:1595930264
DOI:10.1145/1080173
- Conference Chairs:
- Subhabrata Sen,
- Chuanyi Ji,
- Debanjan Saha,
- Joe McCloskey
Copyright © 2005 ACM.
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Association for Computing Machinery
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Publication History
Published: 22 August 2005
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