The Impact of Data Selection Strategies on Distributed Model Performance

Author:

Guimarães MiguelORCID,Oliveira FilipeORCID,Carneiro DavideORCID,Novais PauloORCID

Publisher

Springer Nature Switzerland

Reference11 articles.

1. Alcobaça, E., Siqueira, F., Rivolli, A., Garcia, L.P.F., Oliva, J.T., de Carvalho, A.C.P.L.F.: MFE: towards reproducible meta-feature extraction. J. Machine Learn. Res. 21(111), 1–5 (2020). http://jmlr.org/papers/v21/19-348.html

2. Guimarães, M., et al.: Predicting model training time to optimize distributed machine learning applications. Electronics 12(4), 871 (2023)

3. Hunt, P., Konar, M., Junqueira, F.P., Reed, B.: ZooKeeper: wait-free coordination for internet-scale systems. In: USENIX Annual Technical Conference, vol. 8 (2010)

4. Lauener, J., Sliwinski, W., Cern, G.: How to design & implement a modern communication middleware based on ZeroMQ. In: Proceedings of ICALEPCS, vol. 17, pp. 45–51 (2017)

5. Liu, J., et al.: From distributed machine learning to federated learning: a survey. Knowl. Inf. Syst. 64(4), 885–917 (2022)

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