论文笔记 – Adversarial Training for Weakly Supervised Event Detection.
Wang, Xiaozhi, et al. “Adversarial Training for W …
论文笔记 – Adversarial Training for Weakly Supervised Event Detection. Read More »
学术
论文笔记 – Model-agnostic meta-learning for fast adaptation of deep networks
Finn, Chelsea, Pieter Abbeel, and Sergey Levine. “ …
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论文笔记 – Optimization as a Model for Few-Shot Learning
Ravi, Sachin, and Hugo Larochelle. “Optimization …
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论文笔记 – Learning to Compare: Relation Network for Few-Shot Learning
Sung, Flood, et al. “Learning to Compare: Relatio …
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论文笔记 – Siamese neural networks for one-shot image recognition
Koch Gregory, Richard Zemel, and Ruslan Salakhutdinov. …
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论文笔记 – Prototypical Networks for Few-shot Learning
Snell, Jake, Kevin Swersky, and Richard S. Zemel. ̶ …
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论文笔记 – Matching networks for one shot learning
Vinyals, Oriol, et al. “Matching networks for one …
论文笔记 – Few-shot Slot Tagging with Collapsed Dependency Transfer and Label-enhanced TapNet
Yutai Hou, et al, “Few-shot Slot Tagging with Col …
论文笔记 – A Novel Cascade Binary Tagging Framework for Relational Triple Extraction
Zhepei Wei, et al, “A Novel Cascade Binary Taggin …
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论文笔记 – Extracting Relational Facts by an End-to-End Neural Model with Copy Mechanism
[mathjax] Zeng, Xiangrong, et al. “Extracting Rel …
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