Possible Thesis Topics with Oliver Schulte (August 2018)
I am researching machine learning for structured data, SQL, XML, network data, event logs, sports data.Application Areas
Structured machine learning has many exciting application areas. I am especially interested in the following.- Statistical Modelling of Sports Data. E.g. player ranking, drafting decisions, match outcome prediction.
- Detecting Relationships in Computer Vision.
- Extracting Relationships from Text and Images.
- Anomaly Detection, Data Cleaning.
- Business Process Mining (see the BPM challenge ).
- challenge competitions for structured data like the Yelp Dataset Challenge .
Relational Learning.
An important type of structured data are relational and network data. Topics include:- Learning Bayesian networks. We use these to model the joint distribution of object attributes and links, and for feature generation.
- Classification.
- Anomaly Detection and Exception Mining.
Scaling to hundreds of features (attributes and relationship types) is one of the research topics I would like to work on. This combines systems tools (e.g. Spark, Hadoop) with machine learning. Another important topic is applying our methods to improve node embeddings , a state-of-the-art approach that combines deep learning with networks.