Welcome to Distributed Signal Processing
Description:
In the course Distributed Signal Processing, attention will be paid to decentralized signal processing techniques. Due to the explosion in size and complexity of modern datasets, it is increasingly important to be able to solve problems with a very large number of features or training examples. In industry, this trend has been referred to as ‘Big Data’, and it has had a significant impact in areas as varied as artificial intelligence, internet applications, computational biology, medicine, finance, marketing, journalism, network analysis, weather forecast, telecommunication, and logistics. As a result, both decentralized collection or storage of these datasets, as well as accompanying distributed solution methods are either necessary or at least highly desirable. In this course we will focus on two signal processing techniques for decentralized processing: distributed average consensus algorithms and, more general, distributed optimization algorithms. The problem of distributed averaging on a network comes up in many applications such as coordination of autonomous agents, estimation, and distributed data fusion on ad-hoc networks, and as part of decentralized optimization.
We will consider the following topics: synchronous and asynchronous versions of distributes averaging, gossip algorithms (randomized, geographic, broadcast, etc.), convex optimization, dual ascent, dual decomposition, alternating direction method of multipliers (ADMM) and primal-dual method of multipliers (PDMM).
Prerequisites:
A basic knowledge of mathematics as obtained through undergraduate engineering studies, in particular linear algebra and calculus
Program:
Monday April 4 (Room 4.513): Introduction/distributed averaging
Tuesday April 5 (Room 4.315): Gossip algorithms/convex optimization
Wednesday April 6 (Room 4.513): Convex optimization/decentralized optimization
Thursday April 7 (Room 3.429): Decentralized optimization
Friday April 8 (Room 4.513): Decentralized optimization/applications
Lectures are given from 9:00-12:00 and 13:00-14:30.
The course includes a mini project.
Organizer: Professor Mads Græsbøll Christensen (mgc@create.aau.dk)
Lecturer: Guest Professor Richard Heusdens (rihe@create.aau.dk)
ECTS: 3.0
Time: April 4-8, 2016
Place: Rendsburggade 14
Zip code: 9000
City: Aalborg
Number of seats: 25
Deadline: March 14, 2016
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.
- Teacher: Mads Græsbøll Christensen
- Teacher: Richard Heusdens