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Learning with Marginalized Corrupted Features

Learning with Marginalized Corrupted Features

This video was recorded at International Workshop on Advances in Regularization, Optimization, Kernel Methods and Support Vector Machines (ROKS): theory and applications, Leuven 2013. We propose a new framework for regularization, called marginalized corrupted features, that reduces overfitting by increasing the robustness of the model to data corruptions.... Show More


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