Supervised Distributed Computing: Efficiency and Robustness under a Majority of Adversarial Workers
J. Augustine, H. Hillebrandt, M. Kumar, C. Scheideler, J. Werthmann, in: Proceedings of the ACM Symposium on Principles of Distributed Computing, ACM, 2026.
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Augustine, John;
Hillebrandt, HenningLibreCat;
Kumar, Manish;
Scheideler, ChristianLibreCat;
Werthmann, JulianLibreCat
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Proceedings of the ACM Symposium on Principles of Distributed Computing
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Augustine J, Hillebrandt H, Kumar M, Scheideler C, Werthmann J. Supervised Distributed Computing: Efficiency and Robustness under a Majority of Adversarial Workers. In: Proceedings of the ACM Symposium on Principles of Distributed Computing. ACM; 2026. doi:10.1145/3796701.3815939
Augustine, J., Hillebrandt, H., Kumar, M., Scheideler, C., & Werthmann, J. (2026). Supervised Distributed Computing: Efficiency and Robustness under a Majority of Adversarial Workers. Proceedings of the ACM Symposium on Principles of Distributed Computing. https://doi.org/10.1145/3796701.3815939
@inproceedings{Augustine_Hillebrandt_Kumar_Scheideler_Werthmann_2026, title={Supervised Distributed Computing: Efficiency and Robustness under a Majority of Adversarial Workers}, DOI={10.1145/3796701.3815939}, booktitle={Proceedings of the ACM Symposium on Principles of Distributed Computing}, publisher={ACM}, author={Augustine, John and Hillebrandt, Henning and Kumar, Manish and Scheideler, Christian and Werthmann, Julian}, year={2026} }
Augustine, John, Henning Hillebrandt, Manish Kumar, Christian Scheideler, and Julian Werthmann. “Supervised Distributed Computing: Efficiency and Robustness under a Majority of Adversarial Workers.” In Proceedings of the ACM Symposium on Principles of Distributed Computing. ACM, 2026. https://doi.org/10.1145/3796701.3815939.
J. Augustine, H. Hillebrandt, M. Kumar, C. Scheideler, and J. Werthmann, “Supervised Distributed Computing: Efficiency and Robustness under a Majority of Adversarial Workers,” 2026, doi: 10.1145/3796701.3815939.
Augustine, John, et al. “Supervised Distributed Computing: Efficiency and Robustness under a Majority of Adversarial Workers.” Proceedings of the ACM Symposium on Principles of Distributed Computing, ACM, 2026, doi:10.1145/3796701.3815939.
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