Lecture
This lecture covers the explicit and implicit control of complexity in hypothesis spaces, including variables, polynomial functions, spline functions, wavelet approximations, and RKHS bandwidth. It also discusses risk decomposition, the approximation-estimation trade-off, overfitting, regularization, prediction error, bias-variance tradeoff, and the complexity of models.