Material Detail
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
Quality
- User Rating
- Comments
- Learning Exercises
- Bookmark Collections
- Course ePortfolios
- Accessibility Info