Lukas Einhaus, M. Sc.

Lukas Einhaus, M.Sc. works since April 2020 as a researcher and PhD student at the Embedded Systems department of the University of Duisburg-Essen. After his Bachelors thesis about programming abstractions for concurrent embedded systems he received his Masters degree with a focus on distributed, reliable systems at the University Duisburg-Essen. In his Masters thesis he did research on quantizing neural networks.
My research focuses on techniques for designing neural networks that allow for an efficient implementation in hardware, especially on FPGAs. My main interest herein lies on so called quantized or low precision neural networks. These differ from conventional full precision networks in the heavily reduced bit depth used for computational operations or the representation of the information flow.
47057 Duisburg
Functions
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Wissenschaftliche/r Mitarbeiter/in, Eingebettete Systeme der Informatik
Current lectures
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2022 SS
Past lectures (max. 10)
The following publications are listed in the online university bibliography of the University of Duisburg-Essen. Further information may also be found on the person's personal web pages.
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Elastic AI : System support for adaptive machine learning in pervasive computing systemsIn: CCF Transactions on Pervasive Computing and Interaction Vol. 3 (2021) Nr. 3, pp. 300 - 328
ISSN: 2524-5228; 2524-521XOnline Full Text: dx.doi.org/ (Open Access) -
In-Situ Artificial Intelligence for Self-∗ Devices : The Elastic AI Ecosystem (Tutorial)In: 2nd IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion, ACSOS-C 2021: Proceedings / 2nd IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion, ACSOS-C 2021, Virtual, Washington, 27 September - 1 October 2021 2021, pp. 320 - 321
ISBN: 978-1-6654-4393-7; 978-1-6654-4394-4Online Full Text: dx.doi.org/ -
Towards Precomputed 1D-Convolutional Layers for Embedded FPGAsIn: Machine Learning and Principles and Practice of Knowledge Discovery in Databases: Proceedings, Part I / International Workshops of ECML PKDD 2021, Virtual Event, September 13-17, 2021 / Kamp, Michael; Koprinska, Irena; Bibal, Adrien; Bouadi, Tassadit; Frénay, Benoît; Galárraga, Luis; Oramas, José.; Adilova, Linara; Krishnamurthy, Yamuna; Kang, Bo; Largeron, Christine; Lijffijt, Jefrey; Viard, Tiphaine; Welke, Pascal; Ruocco, Massimiliano; Aune, Erlend; Gallicchio, Claudio; Schiele, Gregor; Pernkopf, Franz; Blott, Michaela; Fröning, Holger; Schindler, Günther; Guidotti, Riccardo; Monreale, Anna; Rinzivillo, Salvatore; Biecek, Przemyslaw; Ntoutsi, Eirini; Pechenizkiy, Mykola; Rosenhahn, Bodo; Buckley, Christopher; Cialfi, Daniela; Lanillos, Pablo; Ramstead, Maxwell; Verbelen, Tim; Ferreira, Pedro M.; Andresini, Giuseppina; Malerba, Donato; Medeiros, Ibéria; Fournier-Viger, Philippe; Nawaz, M. Saqib; Ventura, Sebastian; Sun, Meng; Zhou, Min; Bitetta, Valerio; Bordino, Ilaria; Ferretti, Andrea; Gullo, Francesco; Ponti, Giovanni; Severini, Lorenzo; Ribeiro, Rita; Gama, João; Gavaldà, Ricard; Cooper, Lee; Ghazaleh, Naghmeh; Richiardi, Jonas; Roqueiro, Damian; Saldana Miranda, Diego; Sechidis, Konstantinos; Graça, Guilherme (Eds.) 2021, pp. 327 - 338
ISBN: 978-3-030-93736-2; 978-3-030-93735-5; 978-3-030-93737-9Online Full Text: dx.doi.org/