Location: Conferences » Other » International Workshop on Advances in Regularization, Optimization, Kernel Methods and Support Vector Machines (ROKS): theory and applications, Leuven 2013

Learning with Marginalized Corrupted Features

author: Laurens van der Maaten, Delft University of Technology (TU Delft)
published: Aug. 26, 2013,   recorded: July 2013,   views: 4712
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Description

We propose a new framework for regularization, called marginalized corrupted features, that reduces over fitting by increasing the robustness of the model to data corruptions.

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