Kujifunza kwa Shirikisho la Pamoja
Kujifunza kwa Shirikisho la Pamoja huunganisha usambazaji unaohifadhi faragha wa kujifunza kwa shirikisho na mkusanyiko wa pamoja: kila mteja anayeshiriki hufunza modeli yake ya ndani kwenye data ya faragha, na seva hukusanya utabiri — au vigezo vya modeli — kutoka kwa wateja wote kwa kutumia mikakati ya pamoja kama vile kupiga kura, kupima wastani, au kuweka safu, badala ya wastani wa kigezo pekee.
Soma mbinu kamili
Ingia kwa akaunti ya bure ili kusoma sehemu hii.
Method map
The neighbourhood of related methods — select a node to explore.
Vyanzo
- McMahan, H. B., Moore, E., Ramage, D., Hampson, S., & y Arcas, B. A. (2017). Communication-efficient learning of deep networks from decentralized data. In Proceedings of the 20th International Conference on Artificial Intelligence and Statistics (AISTATS), PMLR 54, 1273–1282. link ↗
- Chen, Y., Qin, X., Wang, J., Yu, C., & Gao, W. (2021). FedHealth: A federated transfer learning framework for wearable healthcare. IEEE Intelligent Systems, 35(4), 83–93. DOI: 10.1109/MIS.2020.2988604 ↗
Jinsi ya kunukuu ukurasa huu
ScholarGate. (2026, June 3). Ensemble Federated Learning (Federated Ensemble Aggregation). ScholarGate. https://scholargate.app/sw/machine-learning/ensemble-federated-learning
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
- Bagging (Bootstrap Aggregating)Ujifunzaji wa Mashine↔ compare
- KuimarishaUjifunzaji wa Mashine↔ compare
- Federated LearningFaragha↔ compare
- Uwekaji juuUjifunzaji wa Mashine↔ compare
- Kujifunza kwa uhamishajiUjifunzaji wa Mashine↔ compare
- Kikundi cha Kura (Voting Ensemble)Ujifunzaji wa Mashine↔ compare
Umeona tatizo kwenye ukurasa huu? Ripoti au pendekeza marekebisho →