HowFine-TuningAllowsforEffectiveMeta-Learning

Neural Information Processing Systems 

We illustrate these bounds in the logistic regression and neural network settings. In contrast, we establish settings where learning one representation for all tasks (i.e. using a "frozen representation" objective) fails. Notably, any such algorithm cannot outperform directly learning the target task with no other information, in the worst case.

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