FedAVL: Automated Vertical Federated Learning for Heterogeneous Healthcare Data

Ferdinand Kahenga; Gad Tambwe; Antoine Bagula; Jovita Mateus; Sajal K. Das

doi:10.1109/SmartComp69968.2026.00014

FedAVL: Automated Vertical Federated Learning for Heterogeneous Healthcare Data

Ferdinand Kahenga
, Gad Tambwe
, Antoine Bagula
, Jovita Mateus
, Sajal K. Das

Computer Science

University of the Western Cape
Université Don Bosco de Lubumbashi (UDBL)
Université Nouveaux Horizons

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Original language	English
Title of host publication	Proceedings - 2026 IEEE International Conference on Smart Computing, SMARTCOMP 2026
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	17-23
Number of pages	7
ISBN (Electronic)	9798319505217
DOIs	https://doi.org/10.1109/SmartComp69968.2026.00014
State	Published - 2026
Event	12th IEEE International Conference on Smart Computing, SMARTCOMP 2026 - Messina, Italy Duration: Jun 22 2026 → Jun 25 2026

Publication series

Name	Proceedings - 2026 IEEE International Conference on Smart Computing, SMARTCOMP 2026

Conference

Conference	12th IEEE International Conference on Smart Computing, SMARTCOMP 2026
Country/Territory	Italy
City	Messina
Period	6/22/26 → 6/25/26

ASJC Scopus Subject Areas

Artificial Intelligence
Computer Science Applications
Computer Vision and Pattern Recognition
Control and Optimization

Keywords

Automated Machine Learning
Healthcare
Optimization
Vertical Federated Learning

Access to Document

10.1109/SmartComp69968.2026.00014

Cite this

Kahenga, F., Tambwe, G., Bagula, A., Mateus, J., & Das, S. K. (2026). FedAVL: Automated Vertical Federated Learning for Heterogeneous Healthcare Data. In Proceedings - 2026 IEEE International Conference on Smart Computing, SMARTCOMP 2026 (pp. 17-23). (Proceedings - 2026 IEEE International Conference on Smart Computing, SMARTCOMP 2026). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SmartComp69968.2026.00014

FedAVL: Automated Vertical Federated Learning for Heterogeneous Healthcare Data. / Kahenga, Ferdinand; Tambwe, Gad; Bagula, Antoine et al.
Proceedings - 2026 IEEE International Conference on Smart Computing, SMARTCOMP 2026. Institute of Electrical and Electronics Engineers Inc., 2026. p. 17-23 (Proceedings - 2026 IEEE International Conference on Smart Computing, SMARTCOMP 2026).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Kahenga, F, Tambwe, G, Bagula, A, Mateus, J & Das, SK 2026, FedAVL: Automated Vertical Federated Learning for Heterogeneous Healthcare Data. in Proceedings - 2026 IEEE International Conference on Smart Computing, SMARTCOMP 2026. Proceedings - 2026 IEEE International Conference on Smart Computing, SMARTCOMP 2026, Institute of Electrical and Electronics Engineers Inc., pp. 17-23, 12th IEEE International Conference on Smart Computing, SMARTCOMP 2026, Messina, Italy, 6/22/26. https://doi.org/10.1109/SmartComp69968.2026.00014

Kahenga F, Tambwe G, Bagula A, Mateus J, Das SK. FedAVL: Automated Vertical Federated Learning for Heterogeneous Healthcare Data. In Proceedings - 2026 IEEE International Conference on Smart Computing, SMARTCOMP 2026. Institute of Electrical and Electronics Engineers Inc. 2026. p. 17-23. (Proceedings - 2026 IEEE International Conference on Smart Computing, SMARTCOMP 2026). doi: 10.1109/SmartComp69968.2026.00014

Kahenga, Ferdinand ; Tambwe, Gad ; Bagula, Antoine et al. / FedAVL : Automated Vertical Federated Learning for Heterogeneous Healthcare Data. Proceedings - 2026 IEEE International Conference on Smart Computing, SMARTCOMP 2026. Institute of Electrical and Electronics Engineers Inc., 2026. pp. 17-23 (Proceedings - 2026 IEEE International Conference on Smart Computing, SMARTCOMP 2026).

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title = "FedAVL: Automated Vertical Federated Learning for Heterogeneous Healthcare Data",

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author = "Ferdinand Kahenga and Gad Tambwe and Antoine Bagula and Jovita Mateus and Das, \{Sajal K.\}",

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FedAVL: Automated Vertical Federated Learning for Heterogeneous Healthcare Data

Publication series

Conference

ASJC Scopus Subject Areas

Keywords

Access to Document

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