About:
The next KE Hub online Triage Workshop will be presented by Dstl.
Generating data for graph machine learning
With the world becoming ever more connected and our reliance on this connectivity increasing, Dstl have an enduring need to efficiently analyse and interpret network structured data. Graph machine learning (ML) techniques have been popular in the data science community and have promise in several tasks such as link prediction and node classification. However, like all ML techniques, they rely on copious amounts of quality labelled data to perform well. Dstl need to devise a strategy for generating synthetic training data for these ML tasks. By generating synthetic and representative data, pitfalls like overfitting can be avoided and models can be applied to unseen data.
This workshop’s challenge is to discuss ideas for an approach to scalable and efficient data generation for network analysis tasks. Dstl’s scenario models networks in one domain where they are scale-free, directed, large (up to 106 nodes), with a pre-specified degree distribution, and with node attributes. Specifically, generating network topologies which match a specified degree distribution lowers the quality of synthetic data as it fails to reproduce other characteristics of the real networks. One should consider the generation technique, its cost in terms of time and computer (memory) resource, and its format.
© Crown copyright (2024), Dstl. This information is licensed under the Open Government Licence v3.0. To view this licence, visit https://www.nationalarchives.gov.uk/doc/open-government-licence/. Where we have identified any third party copyright information you will need to obtain permission from the copyright holders concerned. Any enquiries regarding this publication should be sent to: Dstl.
Academic mathematical scientists from KE Hub partner university departments are invited to take part in these workshops. If you would like to attend, please contact your local KE Champion to receive the meeting link or get in touch with the organisers, Lauren Hyndman and Diwei Zhou.
KE Hub Triage Workshops are informal discussion sessions where one B.I.G. Partner presents a challenge they are currently facing, with the aim of determining:
- What, if any, mathematical sciences approaches can be used to address the challenge?
- Who from the mathematical sciences community would like to take on the challenge?
- What mechanisms are most appropriate for driving the challenge forward?
The purpose of these workshops is to allow the B.I.G. Partner to engage directly with academic mathematical scientists to probe the scientific content of their proposed challenge. The environment is relaxed and interactive, and we encourage questions, clarifications and discussions throughout. You can find information on all upcoming and past workshops here.