The Audio Analysis Lab is organizing a Ph.D. course on Distributed Signal Processing at Aalborg University in the Spring of 2014. The course will be given by Richard Heusdens who is Guest Professor at Aalborg University.

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 the 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: one based on graphical models and one based on convex optimization. We will consider the following topics: graphical models, probabilistic inference, message passing, min-sum/max-product algorithm, Jacobi and Gauss-Seidel algorithm, convex optimization, gossip algorithm, dual ascent, dual decomposition and alternating direction method of multipliers (ADMM).

The course will run April 4-8. If you are interested in following the course, sign up at http://phd.moodle.aau.dk/ or https://phdcourses.dk/ or send course organizer Mads Græsbøll Christensen an email at mgc@create.aau.dk.