【論文精讀】The Devil is the Classifier: Investigating Long Tail Relation Classification with Decoupling
這篇文章是浙江大學2020年9月15號推到Arxiv上的。 文章的初始出發點應該是來自，關係抽取數據集由於數據存在長尾特徵，因此直接從數據中學習語義，必定是不均衡的【樣本多的語義容易過擬合某個類別中的頭部樣本，樣本少的語義容易過擬合某個類別中的單個樣本】。 因此採用引入外部預訓練的詞向量來進行語義embedding就說得通。 同時又知道，我們有三種採樣的方式，來進行長尾數據集的再平衡，即將長尾數據
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相關文章
- 1. The Devil is in the Channels: Mutual-Channel Loss for Fine-Grained Image Classification
- 2. [zz]The Synchronizes-With Relation
- 3. The Devil Wears Prada-16
- 4. 關於「長尾理論」（The Long Tail）
- 5. The Happens-Before Relation | The Synchronizes-With Relation
- 6. 【論文精讀】TACRED Revisited: A Thorough Evaluation of the TACRED Relation Extraction Task
- 7. The Devil is in the Details: Nuances of Light Mapping
- 8. Overcoming Classifier Imbalance for Long-tail Object Detection with Balanced Group Softmax(CVPR20)
- 9. ColorNet: Investigating the importance of color spaces for image classification
- 10. Attention-Based Bidirectional Long Short-Term Memory Networks for Relation Classification 論文研讀