@inproceedings{1aa22781bda341829e6086cbc57d3969,
title = "Diffusion LMS for multitask problems with overlapping hypothesis subspaces",
abstract = "There are many important applications that are multitask-oriented in the sense that there are multiple optimum parameter vectors to be inferred simultaneously by networked agents. In this paper, we formulate an online multitask learning problem where node hypothesis spaces partly overlap. A cooperative algorithm based on diffusion adaptation is derived. Some results on its stability and convergence properties are also provided. Simulations are conducted to illustrate the theoretical results.",
keywords = "collaborative processing, diffusion strategy, distributed optimization, Multitask learning",
author = "Jie Chen and Cedric Richard and Hero, {Alfred O.} and Sayed, {Ali H.}",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 2014 24th IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2014 ; Conference date: 21-09-2014 Through 24-09-2014",
year = "2014",
month = nov,
day = "14",
doi = "10.1109/MLSP.2014.6958929",
language = "英语",
series = "IEEE International Workshop on Machine Learning for Signal Processing, MLSP",
publisher = "IEEE Computer Society",
editor = "Mamadou Mboup and Tulay Adali and Eric Moreau and Jan Larsen",
booktitle = "IEEE International Workshop on Machine Learning for Signal Processing, MLSP",
}