Metodebevisregister

Online Learning

Online learning is a machine learning paradigm in which a model is updated incrementally as each new data point arrives, rather than being trained once on a fixed dataset. It is essential when data streams continuously, storage is limited, or the underlying distribution shifts over time. Theoretical performance is measured by cumulative regret relative to the best fixed predictor in hindsight.

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Online Learning (Sequential / Incremental Machine Learning)

Taksonomisk metoderegister · ml-model / machine-learning

Shalev-Shwartz, S. (2011). Online Learning and Online Convex Optimization. Foundations and Trends in Machine Learning, 4(2), 107–194. · DOI 10.1561/2200000018
Cesa-Bianchi, N. & Lugosi, G. (2006). Prediction, Learning, and Games. Cambridge University Press. · ISBN 978-0-521-84108-5

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