@inproceedings{9cd09134ddba4b5dab00b4af3b204dd6,
title = "Diffusion LMS for clustered multitask networks",
abstract = "Recent research works on distributed adaptive networks have intensively studied the case where the nodes estimate a common parameter vector collaboratively. However, there are many applications that are multitask-oriented in the sense that there are multiple parameter vectors that need to be inferred simultaneously. In this paper, we employ diffusion strategies to develop distributed algorithms that address clustered multitask problems by minimizing an appropriate mean-square error criterion with ℓ2-regularization. Some results on the mean-square stability and convergence of the algorithm are also provided. Simulations are conducted to illustrate the theoretical findings.",
keywords = "Multitask learning, collaborative processing, diffusion strategy, distributed optimization, regularization",
author = "Jie Chen and Cedric Richard and Sayed, \{Ali H.\}",
year = "2014",
doi = "10.1109/ICASSP.2014.6854652",
language = "英语",
isbn = "9781479928927",
series = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "5487--5491",
booktitle = "2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014",
note = "2014 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2014 ; Conference date: 04-05-2014 Through 09-05-2014",
}