Least Square Regularized Regression for Multitask Learning

The study of multitask learning algorithms is one of very important issues. This paper proposes a least-square regularized regression algorithm for multi-task learning with hypothesis space being the union of a sequence of Hilbert spaces. The algorithm consists of two steps of selecting the optimal...

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Bibliographic Details
Main Authors: Yong-Li Xu, Di-Rong Chen, Han-Xiong Li
Format: Article
Language:English
Published: Hindawi Limited 2013-01-01
Series:Abstract and Applied Analysis
Online Access:http://dx.doi.org/10.1155/2013/715275