Adaptive Gradient Methods with Dynamic Bound of Learning Rate
北大和浙大本科生的這篇ICLR論文所提出的優化算法被媒體稱爲」拳打Adam，腳踢SGD「，該工作爲他們在滴滴AI實驗室實習時完成。這篇論文提出了兩種優化算法，分別是Adabound和AMSBound，兩個算法分別是Adam和AMSGrad的變體。在概括這篇論文的研究之前，首先介紹一下Adam和AMSGrad。 本文傳送機 回顧之Adam 回顧之AMSGrad 論文內容 Abstract Intro
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相關文章
- 1. ADADELTA AN ADAPTIVE LEARNING RATE METHOD
- 2. A review of gradient descent optimization methods
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- 10. learning rate