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Oznake: computer science;machine learning;active learning
We present and analyze an active learning algorithm that is theoretically sound in an agnostic setting, empirically effective, and as efficient as standard online learning algorithms. This allows us to soundly and effectively optimize the explore/exploit trade-off in active learning at a scale of 10 ...
Leto: 2011 Vir: videolectures.net
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In this paper we perform an empirical evaluation of supervised learning methods on high dimensional data. We evaluate learning performance on three metrics: accuracy, AUC, and squared loss. We also study the effect of increasing dimensionality on the relative performance of the learning algorithms. ...
Leto: 2008 Vir: videolectures.net
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Oznake: computer science;machine learning
Prediction suffix trees (PSTs) are a popular tool for modeling sequences and have been successfully applied in many domains such as compression and language modeling. In this work we adapt the well studied Winnow algorithm to the task of learning PSTs. The proposed algorithm automatically grows the ...
Leto: 2009 Vir: videolectures.net
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Oznake: computer science;machine learning;on-line learning
Leto: 2010 Vir: videolectures.net
Video in druga učna gradiva
Oznake: computer science;machine learning;computational learning theory
Leto: 2010 Vir: videolectures.net
Št. zadetkov: 5
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