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Email:
daniel.boiar
tu-dortmund.de
Telefon: 0231/755-8257 Telefax: 0231/755-5105 Raumnummer: OH12 R4.011 |
| Sachweh/etal/2022a | Timon Sachweh and Daniel Boiar and Thomas Liebig. Distributed LSTM-Learning from Differentially Private Label Proportions. In Data Mining Workshops, 2022. ICDMW'22. IEEE International Conference on, Seiten (accepted), IEEE, 2022. |
| Boiar/etal/2022a | Daniel Boiar and Nils Killich and Lukas Schulte and Victor Hernandez Moreno and Jochen Deuse and Thomas Liebig. Forecasting Algae Growth in Photo-Bioreactors using Attention LSTMs. In Proceedings of the Workshop on Artificial Intelligence for Engineering Applications 2022, Seiten (accepted), Springer, 2022. |
| Sachweh/etal/2021a | Timon Sachweh and Daniel Boiar and Thomas Liebig. Differentially Private Learning from Label Proportions. In Proceedings of the ECML Workshop on Parallel, Distributed, and Federated Learning, Seiten accepted, 2021. |
| Boiar/2018a | Boiar, Daniel. Realzeitliche Vorhersagen mit Hoeffding-Trees im Tunnelbau. TU Dortmund, 2018. |