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Jdd study 20191127

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JDD study 資料です.

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Jdd study 20191127

  1. 1. 林祐輔 | 2019年11月27日 メタ学習 〜ノーフリーランチ定理を超えて マルチタスクを解く〜
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  4. 4. High-capacity models, such as deep neural networks, have enabled very powerful machine learning techniques in domains where data is plentiful. However, domains where data is scarce have proven challenging for such methods because high-capacity function approximators critically rely on large datasets for generalization. Meta-learning offers a potential solution to this problem: by learning to learn across data from many previous tasks, few-shot meta-learning algorithms can discover the structure among tasks to enable fast learning of new tasks. Meta-learning
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  15. 15. 18 Memory
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  18. 18. Thank you!

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