POKA, Venkateswarlu, 2025. Optimizing AI/ML Model Deployment Across Distributed Systems: Advances in Training Efficiency, Inference Performance, and Fault Tolerance. Journal of Computational Analysis & Applications. 25 Dezember 2025. Vol. 34, no. 11, p. 580-588. DOI 10.48047/jocaaa.2025.34.11.39.
Elsevier - Harvard (with titles)Poka, V., 2025. Optimizing AI/ML Model Deployment Across Distributed Systems: Advances in Training Efficiency, Inference Performance, and Fault Tolerance. Journal of Computational Analysis & Applications 34, 580-588. https://doi.org/10.48047/jocaaa.2025.34.11.39
American Psychological Association 7th editionPoka, V. (2025). Optimizing AI/ML Model Deployment Across Distributed Systems: Advances in Training Efficiency, Inference Performance, and Fault Tolerance. Journal of Computational Analysis & Applications, 34(11), 580-588. https://doi.org/10.48047/jocaaa.2025.34.11.39
Springer - Basic (author-date)Poka V (2025) Optimizing AI/ML Model Deployment Across Distributed Systems: Advances in Training Efficiency, Inference Performance, and Fault Tolerance.. Journal of Computational Analysis & Applications 34:580-588. https://doi.org/10.48047/jocaaa.2025.34.11.39
Juristische Zitierweise (Stüber) (Deutsch)Poka, Venkateswarlu, Optimizing AI/ML Model Deployment Across Distributed Systems: Advances in Training Efficiency, Inference Performance, and Fault Tolerance., Journal of Computational Analysis & Applications 2025, 580-588.