Computationally Efficient Multi-task Learning with Least-squares Probabilistic Classifiers

Abstract

Probabilistic classification and multi-task learning are two important branches of machine learning research. Probabilistic classification is useful when the ‘confidence’ of decision is necessary. On the other hand, the idea of multi-task learning is beneficial if multiple related learning tasks exist. So far, kernelized logistic regression has been a vital… (More)
DOI: 10.2197/ipsjtcva.3.1

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