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Material Detail

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
Keywords:
videolectures, ocwc, oec
Disciplines:
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More about this material

Material Type:
Presentation
Date Added to MERLOT:
February 10, 2015
Date Modified in MERLOT:
February 10, 2015
Author:
Submitter:
The Open Education Consortium
Primary Audience:
College General Ed, College Lower Division, College Upper Division
Technical Format:
Video
Mobile Compatibility:
Not specified at this time
Language:
English
Cost Involved:
No
Source Code Available:
No
Accessibility Information Available:
Unknown
Creative Commons:
Creative Commons License
This work is licensed under a Attribution-NonCommercial-NoDerivs 3.0 United States

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