A performance evaluation of federated learning algorithms A Nilsson, S Smith, G Ulm, E Gustavsson, M Jirstrand Proceedings of the second workshop on distributed infrastructures for deep …, 2018 | 357 | 2018 |
OODIDA: on-board/off-board distributed real-time data analytics for connected vehicles G Ulm, S Smith, A Nilsson, E Gustavsson, M Jirstrand Data Science and Engineering 6, 102-117, 2021 | 24 | 2021 |
Functional Federated Learning in Erlang (ffl-erl) G Ulm, E Gustavsson, M Jirstrand International Workshop on Functional and Constraint Logic Programming, 162-178, 2018 | 22 | 2018 |
PLC Factory: Automating routine tasks in large-scale PLC software development G Ulm, F Bellorini, D Brodrick, R Fernandes, N Levchenko, DP Fernandez Proc. ICALEPCS 17, 495-500, 2018 | 9 | 2018 |
Active-code replacement in the oodida data analytics platform G Ulm, E Gustavsson, M Jirstrand European conference on parallel processing, 715-719, 2019 | 5* | 2019 |
Contraction Clustering (Raster) G Ulm, E Gustavsson, M Jirstrand International Workshop on Machine Learning, Optimization, and Big Data, 63-75, 2017 | 3* | 2017 |
S-RASTER: contraction clustering for evolving data streams G Ulm, S Smith, A Nilsson, E Gustavsson, M Jirstrand Journal of Big Data 7 (1), 62, 2020 | 2 | 2020 |
Contraction clustering (RASTER): a very fast big data algorithm for sequential and parallel density-based clustering in linear time, constant memory, and a single pass G Ulm, S Smith, A Nilsson, E Gustavsson, M Jirstrand arXiv preprint arXiv:1907.03620, 2019 | 1 | 2019 |
Latency and Throughput in Center versus Edge Stream Processing G Ulm | 1 | 2016 |
Compiling Agda to System Fω in Theory G Ulm | | 2015 |
Limitations of semi-compatibilism: a defence of the principle of non-responsibility G Ulm British Journal of Undergraduate Philosophy 2, 1, 2007 | | 2007 |
Active-CodeReplacementinthe OODIDADataAnalyticsPlatform G Ulm, E Gustavsson, M Jirstrand | | |