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Optimally Combining Classifiers Using Unlabeled Data
Akshay Balsubramani
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Oznake: computer science;machine learning;active learning;computational learning theory;on-line learning;reinforcement learning;semi-supervised learning
We develop a worst-case analysis of aggregation of classifier ensembles for binary classification. The task of predicting to minimize error is formulated as a game played over a given set of unlabeled data (a transductive setting), where prior label information is encoded as constraints on the game. ...
Leto: 2015 Vir: videolectures.net
Št. zadetkov: 1
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