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Bundle methods for regularized risk minimization with applications to robust learning

Teo, Choon-Hui


Supervised learning in general and regularized risk minimization in particular is about solving optimization problem which is jointly defined by a performance measure and a set of labeled training examples. The outcome of learning, a model, is then used mainly for predicting the labels for unlabeled examples in the testing environment. In real-world scenarios: a typical learning process often involves solving a sequence of similar problems with different parameters before a final model is...[Show more]

CollectionsOpen Access Theses
Type: Thesis (PhD)
DOI: 10.25911/5d5156f5459c3


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