Lecture 11: Statistical Estimation
Lecture 11: Sequential Convex Programming
Lecture 6: Least-Squares
Statistical Leverage and Improved Matrix Algorithms
Lecture 8: Lagrangian
Lecture 1: Introduction to Convex Optimization I
Adversarial Examples
Sparse Methods for Machine Learning: Theory and Algorithms
Lecture 15: Recap: Example: Minimum Cardinality Problem
Lecture 7: Generalized Inequality Constraints