Cite
dsMTL: a computational framework for privacy-preserving, distributed multi-task machine learning.
MLA
Cao, Han, et al. “DsMTL: A Computational Framework for Privacy-Preserving, Distributed Multi-Task Machine Learning.” Bioinformatics, vol. 38, no. 21, Nov. 2022, pp. 4919–26. EBSCOhost, https://doi.org/10.1093/bioinformatics/btac616.
APA
Cao, H., Zhang, Y., Baumbach, J., Burton, P. R., Dwyer, D., Koutsouleris, N., Matschinske, J., Marcon, Y., Rajan, S., Rieg, T., Ryser-Welch, P., Späth, J., Consortium, T. C., Herrmann, C., & Schwarz, E. (2022). dsMTL: a computational framework for privacy-preserving, distributed multi-task machine learning. Bioinformatics, 38(21), 4919–4926. https://doi.org/10.1093/bioinformatics/btac616
Chicago
Cao, Han, Youcheng Zhang, Jan Baumbach, Paul R Burton, Dominic Dwyer, Nikolaos Koutsouleris, Julian Matschinske, et al. 2022. “DsMTL: A Computational Framework for Privacy-Preserving, Distributed Multi-Task Machine Learning.” Bioinformatics 38 (21): 4919–26. doi:10.1093/bioinformatics/btac616.