GSP 2013 - 2013 Symposium on: Graph Signal Processing

Applications ranging from the emerging smart grid to social networks, from neuroscience to transportation and telecommunication network monitoring, are giving rise to massive data sets where the data is naturally supported on a graph. In these scenarios the data associated to nodes in the graph can be viewed as a “graph signal” and it is natural to ask whether signal processing techniques and methodologies could be used for dealing with these graph signals. Graph signal processing focuses on the interplay between the graph topology and characteristics of the corresponding signals. The aim of this symposium is to bring together researchers working in the emerging field of graph signal processing to exchange ideas and present their latest results. The symposium will also serve as a forum for researchers in the signal processing community interested in learning about the latest developments in this field.
Submissions of at most 4 pages in two-column IEEE format are welcome on topics including:
Transforms for graph signals
Estimation, denoising, and compression for graph signals
Sparse representations of graph signals
Multi-scale analysis on graphs
Graph signal downsampling and simplification
Uncertainty principles for graph signals
Estimating graph structure from data point-clouds
Graph signal processing in machine learning
Applications of graph signal processing