【論文筆記】Continual Relation Learning via Episodic Memory Activation and Reconsolidation
Continual Relation Learning via Episodic Memory Activation and Reconsolidation Abstract 持續關係學習：不遺忘以前關係的同時繼續學習新關係 新關係的出現會忘記舊的關係，雖然有證明在新的關係訓練序列中添加遺忘的訓練樣本可以避免這個問題，但是又容易陷入over-fitting 因此本文根據人類的長期記憶構成，設計了E
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相關文章
- 1. 論文《Unsupervised Continual Learning And Self-Taught Associative Memory Hierarchies》解讀
- 2. 論文理解—— Disentangle-based Continual Graph Representation Learning
- 3. VITAL: VIsual Tracking via Adversarial Learning論文筆記
- 4. 【論文筆記】Deep Metric Learning via Facility Location
- 5. 論文閱讀筆記《Learning to Compare: Relation Network for Few-Shot Learning》
- 6. Machine Learning & Deep Learning 論文閱讀筆記
- 7. [CVPR 2019 論文筆記] Generalized Zero- and Few-Shot Learning via Aligned Variational Autoencoders
- 8. Two at Once: Enhancing Learning and Generalization Capacities via IBN-Net論文筆記
- 9. 論文閱讀筆記《Generalized Zero- and Few-Shot Learning via Aligned Variational Autoencoders》
- 10. 論文閱讀筆記《Transductive Episodic-Wise Adaptive Metric for Few-Shot Learning》