In Winter 2023–24 we will be using an updated set of slides developed last summer by Parth Nobel and Stephen Boyd.

  1. Introduction

  2. Convex sets

  3. Convex functions

  4. Convex optimization problems

  5. Duality

  6. Approximation and fitting

  7. Statistical estimation

  8. Geometric problems

  9. Numerical linear algebra background

  10. Unconstrained minimization

  11. Equality constrained minimization

  12. Interior-point methods

  13. Conclusions

The full set of slides is available as one PDF file here.

The original slides, used until Summer 2023, are available here.

Additional lecture slides:

  1. Convex optimization examples

  2. Stochastic programming

  3. Chance constrained optimization

  4. Filter design and equalization

Two lectures from EE364b:

  1. L1 methods for convex-cardinality problems

  2. L1 methods for convex-cardinality problems, part II

CVX* tutorial sessions:

  1. Disciplined convex programming and CVX

  2. CVX slides (code)

  3. Convex.jl slides

  4. CVXPY tutorial website

Note that in Winter 2023–24, we will be using an supporting only CVXPY.