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• W2057325524 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." @default.
• W2057325524 created "2016-06-24" @default.
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• W2057325524 date "2014-09-01" @default.
• W2057325524 modified "2023-09-25" @default.
• W2057325524 title "Diffusion LMS for multitask problems with overlapping hypothesis subspaces" @default.
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• W2057325524 doi "https://doi.org/10.1109/mlsp.2014.6958929" @default.
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