Publication: Federated learning as a solution for problems related to intergovernmental data sharing
Federated learning as a solution for problems related to intergovernmental data sharing
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Sprenkamp, K., Delgado Fernandez, J., Eckhardt, S., & Zavolokina, L. (2023, January 6). Federated learning as a solution for problems related to intergovernmental data sharing. 56th Hawaii International Conference on System Sciences, Maui (HI). https://www.researchgate.net/publication/364308366_Federated_Learning_as_a_Solution_for_Problems_Related_to_Intergovernmental_Data_Sharing
Abstract
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To address global problems, intergovernmental collaboration is needed. Modern solutions to these problems often include data-driven methods like artificial intelligence (AI), which require large amounts of data to perform well. However, data sharing between governments is limited. A possible solution is federated learning (FL), a decentralised AI method created to utilise personal information on edge devices. Instead of sharing data, governments can build their own models and just share the model parameters with a centralised server a
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Citations
Sprenkamp, K., Delgado Fernandez, J., Eckhardt, S., & Zavolokina, L. (2023, January 6). Federated learning as a solution for problems related to intergovernmental data sharing. 56th Hawaii International Conference on System Sciences, Maui (HI). https://www.researchgate.net/publication/364308366_Federated_Learning_as_a_Solution_for_Problems_Related_to_Intergovernmental_Data_Sharing