Regularization Methods for Machine Learning

Slides I (latest course offering)

• Statistical Learning Theory

• Tikhonov Regularization and Kernels

• Early Stopping and Spectral Regularization

• Regularization for Multi-Task Learning

• Sparsity Based Regularization

• Structured Sparsity

• Dictionary Learning

• Deep Learning

Slides II (old lessons)

• Kernels, Dictionary and Regularization

• Regularized Least Square and Support Vector Machines

• Regularization via Spectral Filtering

• Manifold Regularization

• Model Selection and Regularization Parameter Choice

• Sparsity Based Regularization

• Regularization with Multiple Kernels

Labs code

• Lab I: Binary Classification and Model Selection

• Lab II: Spectral Filters and Multi-Class Classification

• Lab III: Sparsity based Learning