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Few-short learning (FSL) can be useful for many (if not all) machine learning problems, including supervised learning (regression and classification) and reinforcement learning. The paper Generalizing from a Few Examples: A Survey on Few-Shot Learning (2020) provides an overview (including examples of applications and use cases) of FSL. Their definition of ...


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They use the same techniques, but study different problems. Transfer learning always does not imply that the novel classes have very-few samples (as few as 1 per class). Few-shot learning does. The goal of transfer learning is to obtain transferrable features that can be used for a wide variety of downstream discriminative tasks. One example is using an ...


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