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OSDI'21
https://www.usenix.org/conference/osdi21/presentation/qiao
https://github.com/petuum/adaptdl
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**Problem**
What do you want to do? What is blocking you?
I am reading an article and would like to discuss the possibility of implementing it in the prototypical network (https://arxiv.org/abs/18…
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### Author Pages
https://aclanthology.org/people/h/hui-chen/
### Type of Author Metadata Correction
- [X] The author page wrongly conflates different people with the same name.
- [ ] This author ha…
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## 一言でいうと
経験的に良いと知られていたWarm-up(学習初期で低い学習率を使用する)を自動的に行う手法。Adamのような学習率を自動調整する手法は、学習初期(=まだサンプルがない状態)の調整で誤った方向に誘導されがちなことを指摘。そこで方向(勾配)の分散を抑える調整を導入している
![image](https://user-images.githubusercontent.c…
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What Gradient Descent Method clstm is using? SGD? AdaGrad? NAG? RMSProp? Adam?
I want to increase the speed of the learning.
If clstm is not using adaptive learning rate algorithm, I also have to ask…
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https://virtual2023.aclweb.org/paper_P2036.html
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**Is your feature request related to a problem? Please describe.**
> Despite attractive theoretical guarantees and practical successes, Predictive Interval (PI) given by Conformal Prediction (CP) m…
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Explore and document the methods to achieve responsive design using Tailwind CSS. Tailwind provides utility-first classes that make it easy to implement responsive layouts without writing custom media…
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## 論文リンク
https://arxiv.org/abs/1908.03265
## 公開日(yyyy/mm/dd)
2019/08/08
## 概要
Adam が抱える学習初期に学習率の分散が発散するという問題に着目し、それを解決する RAdam を提案。
経験的に warm up (学習初期は linear でスケールする小さな学習率で学習し、その後に所望の学習率スケジ…