Lectures

We follow closely the textbook Optimization Models. You can also find the livebook useful.

The slides were originally developed by G. Calafiore, then edited by L. El Ghaoui, A. Bayen, and G. Ranade.

• Introduction

• Vectors and functions, vector calculus

• Matrices and linear maps

• QR decomposition and orthogonalization

• Symmertric matrices and their decomposition

• Singular value decomposition

• Linear equations

• Least-squares and variants

• Linear algebra applications

• Linear algebra review

• Convexity

• Convex optimization

• Algorithms

• Linear Optimization

• Quadratic optimization

• Second-order cone optimization

• Robust optimization

• Weak duality

• Strong duality

• Review

• Optimality conditions

• Machine learning applications (I)

• Machine learning applications (II)

• Control applications

• Energy applications