Machine learningTraining paradigms
多任务学习
多任务学习（MTL）是一种机器学习范式，其中一个模型同时在多个相关任务上进行训练，并在它们之间共享表示以提高泛化能力。MTL由Rich Caruana于1997年正式提出，其直觉是辅助任务充当归纳偏置，提供额外的监督信号，帮助共享层学习比单任务训练更丰富、更鲁棒的特征表示。
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来源
- Caruana, R. (1997). Multitask learning. Machine Learning, 28(1), 41–75. DOI: 10.1023/A:1007379606734 ↗
如何引用本页
ScholarGate. (2026, June 2). Multitask Learning. ScholarGate. https://scholargate.app/zh/deep-learning/multitask-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.
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