Linear and Weighted Regression: Optimal Parameters and Local Solutions

This lecture covers linear regression, focusing on finding the optimal parameter w through least-square regression and the closed-form solution. It also introduces weighted regression and locally weighted regression, explaining how to determine the optimal parameter w and the local solution. The application of Support Vector Regression (SVR) for mapping eyes to gaze is discussed, along with the sensitivity of different regression techniques to noise and missing data. The exercise section explores Regular Least Squares, Weighted Least Squares, and Locally Weighted Regression in detail.