Distributed Learning of Predictive Structures from Multiple Tasks Over Networks
Junhao Hua, Chunguang Li, Hui-Liang Shen
IEEE Transactions on Industrial Electronics(TIE, ZJU-TOP100), vol. 64, no.5, pp.4246-4256, May 2017.
We concerned with the problem of distributed multitask learning over networks, which aims to simultaneously
infer multiple node-specific parameter vectors in a collaborative manner. In this work, we implicitly model
the similarity of parameter vectors by assuming that the parameter vectors share a common low-dimensional
predictive structure on hypothesis spaces, which is learned using the available data in networks.
A distributed structure learning algorithm for the in-network cooperative estimation problem is derived
based on the block coordinate descent method integrating with the inexact ADMM technique.