• Splitting methods: Splitting methods in optimisation, proximal methods, and the Alternating Direction Method of Multipliers (ADMM).

  • First order methods: First order methods, minimising sequence, admissible direction, and the Generalised Projected Gradient Descent (again).

  • Mirror descent algorithm: The Generalised Projected Gradient Descent (GPGD) and the Mirror Descent Algorithm (MDA).

  • Projected gradient descent: Normal cone, Euclidean projection, and the Projected Gradient Descent (PGD).

  • Convex analysis – pt. III: Strict and strong convexity, Bregman divergences, and the link between Lipschitz continuity and strong convexity.

  • Convex analysis – pt. II: The convex conjugate, Fenchel's inequality, and the Fenchel-Moreau theorem.

  • Convex analysis – pt. I: The subdifferential and the First-order Optimality Condition (FOC).

  • Convex Optimisation – intro: Introduction to the general convex minimisation problem and generic iterative methods.