Welcome to Distributed Optimisation


In this course, we will discuss  several distributed optimization techniques. We group them into two categories.

The first  category consists of the methods leaning on augmented Lagrangian decomposition. These include Dual Decomposition, the Alternating Direction Method of

Multipliers with Proximal Message Passing, Analytical Target

Cascading, and the Auxiliary Problem Principle. The second category addresses decentralized solution of the Karush-Kuhn-Tucker (KKT)-  necessary conditions for

local optimality. These include Optimality Condition

Decomposition and Consensus+Innovation. 

Prerequisites: Linear algebra or matrix calculus  

Organizer: Professor Rafael Wisniewski

Lecturers: Prof. Richard Heusdens (Delft University of Technology), Prof. Mads Græsbøll Christensen, Prof. Rafael Wisniewski and Associate Prof. John Leth 


Time: November 5 to November 9, 2018



Number of seats: 40

Deadline: October 15, 2018

Important information concerning PhD courses
 We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 5,000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately three months before start. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations


Day 1: Introduction to optimisation by John Leth <jjl@es.aau.dk>