Vorträge und Posterpräsentationen (ohne Tagungsband-Eintrag):
G. Matz:
"Data Science by TV on the Graph";
Vortrag: Workshop on Mathematical Data Science,
Dürnstein (eingeladen);
13.10.2019
- 15.10.2019.
Kurzfassung englisch:
Graph signal processing is a modern paradigm to deal with large data sets. It captures the intrinsic structure of the data via the topology of a graph. By capitalizing on the graph structure, diverse large-scale learning and inference problems can be tackled. Graph signal processing is promising in applications like sensor networks, social networks, infrastructure networks, or biological networks.In this talk I will report some of our recent work in which we build on the notion of graph total variation to formulate a consistent theoretical framework and efficient distributed algorithms for data reconstruction, network structure inference, and clustering.