Interpretable and differentially private predictions F Harder, M Bauer, M Park Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 4083-4090, 2020 | 21 | 2020 |
DP-MERF: Differentially Private Mean Embeddings with RandomFeatures for Practical Privacy-preserving Data Generation F Harder, K Adamczewski, M Park International Conference on Artificial Intelligence and Statistics, 1819-1827, 2021 | 15* | 2021 |
An approach to supervised learning of three valued Lukasiewicz logic in Hölldobler's core method F Harder, TR Besold CEUR Workshop Proceedings 1895, 24-37, 2017 | 1 | 2017 |
Q-FIT: The Quantifiable Feature Importance Technique for Explainable Machine Learning K Adamczewski, F Harder, M Park arXiv preprint arXiv:2010.13872, 2020 | | 2020 |
DP-MAC: The Differentially Private Method of Auxiliary Coordinates for Deep Learning F Harder, J Köhler, M Welling, M Park arXiv preprint arXiv:1910.06924, 2019 | | 2019 |
Learning Łukasiewicz logic F Harder, TR Besold Cognitive Systems Research 47, 42-67, 2018 | | 2018 |