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Regularization for Deep Learning

Regularization for Deep Learning. C. Lee Giles. Thanks to Alexander Ororbia and Sargur Srihari. What is Regularization?. Goals of Regularization. Regularize Your Estimator!. regularizer. Regularization & Model Types. The Value of Regularization. Model family. Finding the Best Model.

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Regularization for Deep Learning

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  1. Regularization for Deep Learning C. Lee Giles Thanks to Alexander Ororbia and Sargur Srihari

  2. What is Regularization?

  3. Goals of Regularization

  4. Regularize Your Estimator! regularizer

  5. Regularization & Model Types

  6. The Value of Regularization Model family

  7. Finding the Best Model

  8. L1 and L2 Unit Balls Unit ball = set of points equidistant to origin Goal = find a way to get to the red line

  9. Dead unit = neuron will never activate on any datapoint again

  10. Augment the data! More robust to adversarial examples

  11. Data augmentation process can be dynamic!

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