Regularized multi--task learning

  title={Regularized multi--task learning},
  author={Theodoros Evgeniou and Massimiliano Pontil},
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 functionals similar to existing ones, such as the one for Support Vector Machines (SVMs), that have been successfully used in the past for single--task learning. Our approach allows to model the… CONTINUE READING
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