The paper of this reseach can be found in the main folder of the repository.
Our experiments are conducted on the Criteo dataset, which can be obtained via (http://www.cs.cornell.edu/~adith/Criteo/).
The contributions of our paper can be found in the NeuralBLBF folder. To train and test a model, the main.py file can be used. The following models are available for usage:
- TinyEmbedFFNN
- SmallEmbedFFNN
- LargeEmbedFFNN
- SparseFFNN
- SparseLinear
- CrossNetwork
The baseline results of the paper: Large-scale Validation of Counterfactual Learning Methods A Test-Bed by Lefortier et al. can be replicated with the POEM and Scripts folder. The code was obtained via the papers related website (http://www.cs.cornell.edu/~adith/Criteo/). The website contains a detailed explanation how the baseline results from the paper can be reproduced.
- Jasper Adegeest - jasper.adegeest@student.uva.nl
- Verna Dankers - verna.dankers@student.uva.nl
- Michiel van der Meer - michiel.vandermeer@student.uva.nl
- Renzo van Slooten - renzo.vanslooten@student.uva.nl