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Pembelajaran Dalam Talian Teguh

Pembelajaran Dalam Talian Teguh (Robust Online Learning) meluaskan rangka kerja pembelajaran dalam talian — di mana model dikemas kini secara berurutan selepas setiap pemerhatian — dengan menggabungkan mekanisme keteguhan yang melindungi daripada label yang rosak, contoh adversarial, hingar ekor berat, dan anjakan konsep. Hasilnya ialah pelajar berurutan yang mengekalkan penyesalan terikat walaupun apabila aliran data mengandungi pencilan atau gangguan yang disengajakan.

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Sumber

  1. Hazan, E. (2016). Introduction to Online Convex Optimization. Foundations and Trends in Optimization, 2(3–4), 157–325. link
  2. Shalev-Shwartz, S. (2012). Online Learning and Online Convex Optimization. Foundations and Trends in Machine Learning, 4(2), 107–194. DOI: 10.1561/2200000018

Cara memetik halaman ini

ScholarGate. (2026, June 3). Robust Online Learning (Adversarially and Noise-Resilient Sequential Learning). ScholarGate. https://scholargate.app/ms/machine-learning/robust-online-learning

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ScholarGateRobust Online Learning (Robust Online Learning (Adversarially and Noise-Resilient Sequential Learning)). Dicapai 2026-06-15 daripada https://scholargate.app/ms/machine-learning/robust-online-learning · Set data: https://doi.org/10.5281/zenodo.20539026