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Ujifunzaji Unganishi wa Mtandaoni

Ujifunzaji Unganishi wa Mtandaoni (OFL) unaunganisha muundo uliogatuliwa, unaohifadhi faragha wa ujifunzaji unganishi na utaratibu wa kusasisha hatua kwa hatua, sampuli kwa sampuli wa ujifunzaji wa mtandaoni. Wateja — kama vile vifaa vya mkononi au vitambuzi vya pembeni — hupokea modeli ya kimataifa, huisasisha kwa data mpya inayowasili bila kushiriki uchunguzi ghafi, na huchangia masasisho yaliyobanwa kwa seva kuu inayoyakusanya kwa wakati halisi.

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Vyanzo

  1. Damaskinos, G., Guerraoui, R., Kermarrec, A.-M., Guirguis, A., Riviere, M., & Tempo, R. (2020). FLEET: Flexible and Efficient Federated Learning for Edge AI. Proceedings of Machine Learning and Systems (MLSys). link
  2. McMahan, B., Moore, E., Ramage, D., Hampson, S., & Aguera y Arcas, B. (2017). Communication-Efficient Learning of Deep Networks from Decentralized Data. Proceedings of the 20th International Conference on Artificial Intelligence and Statistics (AISTATS), 54, 1273–1282. link

Jinsi ya kunukuu ukurasa huu

ScholarGate. (2026, June 3). Online Federated Learning (Sequential Distributed Learning without Centralised Data). ScholarGate. https://scholargate.app/sw/machine-learning/online-federated-learning

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Imerejelewa na

ScholarGateOnline Federated Learning (Online Federated Learning (Sequential Distributed Learning without Centralised Data)). Imepatikana 2026-06-15 kutoka https://scholargate.app/sw/machine-learning/online-federated-learning · Seti ya data: https://doi.org/10.5281/zenodo.20539026