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| Học chuyển giao trực tuyến× | Học trực tuyến× | |
|---|---|---|
| Lĩnh vực | Học máy | Học máy |
| Họ | Machine learning | Machine learning |
| Năm ra đời≠ | 2010 | 1958–2000s |
| Người khởi xướng≠ | Zhao, P. & Hoi, S. C. H. | Rosenblatt, F.; Littlestone, N.; Shalev-Shwartz, S. (key contributors) |
| Loại≠ | Online learning with source-domain knowledge transfer | Learning paradigm (sequential model update) |
| Công trình gốc≠ | Zhao, P., & Hoi, S. C. H. (2010). OTL: A Framework of Online Transfer Learning. In Proceedings of the 27th International Conference on Machine Learning (ICML 2010), pp. 1231–1238. Omnipress. link ↗ | Shalev-Shwartz, S. (2011). Online Learning and Online Convex Optimization. Foundations and Trends in Machine Learning, 4(2), 107–194. DOI ↗ |
| Tên gọi khác | OTL, streaming transfer learning, incremental transfer learning, online domain adaptation | incremental learning, sequential learning, streaming learning, online machine learning |
| Liên quan≠ | 4 | 6 |
| Tóm tắt≠ | Online Transfer Learning (OTL) extends transfer learning to sequential, streaming settings: instead of training on a fixed dataset, the model processes examples one at a time and simultaneously leverages knowledge from a related source domain to improve predictions on the target domain without requiring large labeled target datasets upfront. | 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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