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 <email@example.com>