Bjarne Ørum Fruergaard
|Bjarne Ørum Fruergaard (Bjarne Ørum Wahlgreen)|
|Affiliation:||Section for Cognitive Systems, Technical University of Denmark |
|Databases:||Google Scholar Scopus Twitter (Eyes4ML)|
|Search:||PubMed (first author) PubMed |
His Master Thesis from 2010 was titled Distributed topic modeling of web-scale text corpora, and his PhD Thesis from 2015 was titled Statistical learning for predictive targeting in online advertising which was supervized by Lars Kai Hansen and Jesper Urban.
Wahlgreen has been working with the Responsible Business in the Blogosphere research projects.
He has worked with latent factor log-linear model (LFL). This is a model suggested in A log-linear lodel with latent features for dyadic prediction. He has also worked with the infinite relational model and multiple Poisson stochastic block models.
- Compact web browsing profiles for click-through rate prediction
- Dimensionality reduction for click-through rate prediction: Dense versus sparse representation
- Distributed topic modeling of web-scale text corpora
- Efficient inference of overlapping communities in complex networks
- Large scale topic modeling made practical
- Predicting clicks in online display advertising with latent features and side-information
- Static analysis of concurrent Java Programs