《A Mixture of h-1 Heads is Better than h Heads》论文笔记

时间 2021-01-17

标签 NLP 论文自然语言处理深度学习繁體版

原文原文链接

1、摘要多头注意神经结构已经在各种自然语言处理任务上取得了最先进的结果。事实证明，它们是过度参数化的，注意力头可以被修剪而不会造成显著的性能损失。论文提出：根据输入的不同，选择不同的header，提出了专注其中几个header的专家混合模型(MAE)。 MAE使用block coordinate descent (BCD：块协同下降算法)进行训练，该算法交替更新(1)选择header的参

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1. Two Heads Are Often Better Than One
2. [UVA 545] Heads 题解
3. hook declined to update refs/heads/dev
4. PHP is much better than you think
5. The Rise of Worse Is Better 论文-学习笔记
6. (92) Is there a better crawler than Scrapy? - Quora
7. Why CSS Grid is better than Bootstrap
8. 什么是Heads-up displays（HUD）
9. 【论文笔记】Attention is all you need
10. 【论文阅读笔记】Recursive Unsupervised Learning of Finite Mixture Models

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