Sparse Regression and Convex Optimization

This lecture covers the mathematics behind data analysis, focusing on sparse regression in generalized linear models and the optimization formulations involved. It also delves into the estimation of sparse precision matrices for graphical models, composite convex minimization, proximal operators, and designing algorithms for finding solutions efficiently.