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메타학습 1

Meta-learning 논문 리뷰

1. Learning to learn by gradient descent by gradient descent NeurIPS 2016 Andrychowicz et al. Paper link: https://arxiv.org/pdf/1606.04474.pdf ​Code link: 2. Model-Agnostic Meta-learning for Fast Adaptation of Deep Networks ICML 2017 Finn et al. Paper link: https://arxiv.org/pdf/1703.03400.pdf Code link: model: MAML MAML의 목적은 주어진 meta-learning의 experiences를 이용해서 임의의 task에 대하여 가장 빠르게 학습할 수 있는 mod..

paper summary and review 2022.03.11
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프로필사진

KAIST Mathematical Science / Computer Science. 19

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  • 분류 전체보기 (13)
    • paper list (1)
    • paper summary and review (8)
      • CNN(Convolutional Neural Ne.. (1)
      • Meta-learning(Supervised) (4)
      • Meta-learning(Unsupervised) (0)
    • PRML (4)
      • 3. Linear Models For Regres.. (1)
      • 6. Kernel Methods (3)
      • 8. Graphical Models (0)

Tag

메타학습, MAML, Residual Block, 자기지도학습, Self-supervised Learning, DL paper, neural network, PRML, 딥러닝, Computer Vision, ResNet, Machine Learning, unsupervised learning, ML, Few-Shot learning, ML paper, 머신러닝, deep learning, meta-learning, 메타러닝,

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