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Regularized multi--task learning

Published in Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining • Aug 22, 2004
NobleIDNI3P75W90R13S35
Authors:
Theodoros Evgeniou
,
Massimiliano Pontil

Abstract

Past empirical work has shown that learning multiple related tasks from data simultaneously can be advantageous in terms of predictive performance relative to learning these tasks independently. In this paper we present an approach to multi--task learning based on the minimization of regularization ...

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