This project was conducted during the first year of my master's at Sorbonne Université. The main focus was to find low-complexity methods for the random walk graph kernel, especially on labeled graphs.
- numpy
- scipy
- scikit-learn
- grakel (to import graph databases)
- control (dlyap)
- slycot (necessary for dlyap in control)
- jupyter (optional, for tests)
- Thesis report and presentation slides
- A synthetic graph database generator
- The Random Walk kernel introduced by (Vishwanathan et al, 2010)
- 5 Acceleration Methods introduced in the same paper
- Experiments on their speed and accuracy