Graphs and networked data¶
Learning when the data points are related rather than independent: signals on graphs, recovery from few measurements, and model selection when the network structure is itself unknown.
7 supervised theses. See all supervised theses for the full list, or open topics if you are looking for one to take on.
| Level | Author | Title | Date | Industry | Recording |
|---|---|---|---|---|---|
| MSc | L. Ban | Neural Motif Counting in Uncertain Graphs | May 2024 | ||
| PhD | N. Tran-Quang | Machine Learning for Networked Data | Feb. 2020 | ||
| MSc | H. Ambos | Semi-supervised learning over complex networks | Mar. 2019 | ||
| MSc | O. Abramenko | Graph signal sampling via reinforcement learning | Nov. 2018 | ||
| MSc | S. Basirian Jahromi | Compressed sensing for big data over complex networks | Jan. 2018 | ||
| MSc | A. Mara | A comparative analysis of graph signal recovery methods for big data networks | Oct. 2017 | ||
| MSc | Y. Gao | Graphical model selection in big data application | Dec. 2016 |