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Pembelajaran Aktif Pembelajaran Berfederasi

Pembelajaran Aktif Berfederasi menggabungkan kecekapan anotasi pembelajaran aktif dengan desentralisasi pembelajaran berfederasi yang memelihara privasi. Model global yang dikongsi dilatih merentasi klien teragih, yang setiap satunya secara bebas menilai data tempatan mereka yang tidak berlabel dan meminta label hanya untuk contoh yang paling bermaklumat, sambil menyimpan data mentah pada peranti sepanjang masa.

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Method map

The neighbourhood of related methods — select a node to explore.

Sumber

  1. Ro, J. Y., Ali, A., Lin, Z., & Suresh, A. T. (2021). Scaling Federated Learning for Fine-tuning of Large Language Models. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP). link
  2. Federated learning. Wikipedia. link

Cara memetik halaman ini

ScholarGate. (2026, June 3). Federated Active Learning (Active Learning within Federated Learning). ScholarGate. https://scholargate.app/ms/machine-learning/active-learning-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.

Compare side by side
ScholarGateActive Learning Federated Learning (Federated Active Learning (Active Learning within Federated Learning)). Dicapai 2026-06-15 daripada https://scholargate.app/ms/machine-learning/active-learning-federated-learning · Set data: https://doi.org/10.5281/zenodo.20539026