論文筆記--Meta learning with implicit gradient
Meta-learning with implicit gradients--nips19 論文思想 Few-shot case formula Implicit MAML Algorithm Practical Algorithm 論文思想 原始的MAML算法一個很大的挑戰是外循環（元更新）需要通過對內循環（梯度自適應）過程進行求導，一般就要求存儲和計算高階導數。這篇論文的核心是利用隱微分方法，
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相關文章
- 1. 論文閱讀筆記《Gradient-Based Meta-Learning with Learned Layerwise Metric and Subspace》
- 2. 論文閱讀筆記《Meta-Learning with Temporal Convolutions》
- 3. 論文閱讀筆記《Meta-learning with differentiable closed-form solvers》
- 4. 論文閱讀筆記《Meta-learning with Latent Embedding Optimization》
- 5. 論文閱讀筆記《Meta-Learning with Memory-Augmented Neural Networks》
- 6. 論文閱讀筆記《Auto-Meta: Automated Gradient Based Meta Learner Search》
- 7. Meta Network||論文筆記
- 8. 論文筆記——NEURAL ARCHITECTURE SEARCH WITH REINFORCEMENT LEARNING
- 9. Multi-view Learning with Incomplete Views論文筆記
- 10. Federated Learning with Non-IID Data 論文筆記