Online Gradient Descent – Parameter-free Learning and Optimization Algorithms
Descrição
This post is part of the lecture notes of my class "Introduction to Online Learning" at Boston University, Fall 2019. I will publish two lectures per week. You can find the lectures I published till now here. To summarize what we said in the previous note, let's define online learning as the following general game…
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Optimization for Deep Learning
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Gradient Descent and Adam Optimization
![Online Gradient Descent – Parameter-free Learning and Optimization Algorithms](https://www.ruder.io/content/images/2016/09/sgd_fluctuation.png)
An overview of gradient descent optimization algorithms
![Online Gradient Descent – Parameter-free Learning and Optimization Algorithms](https://parameterfree.files.wordpress.com/2019/09/sum_log.png)
What is Online Learning? – Parameter-free Learning and
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PDF] An overview of gradient descent optimization algorithms
![Online Gradient Descent – Parameter-free Learning and Optimization Algorithms](https://www.researchgate.net/publication/332715365/figure/fig2/AS:962461960241156@1606480221448/Adam-is-an-effective-gradient-descent-algorithm-for-ODEs-a-Using-a-constant-learning.png)
Adam is an effective gradient descent algorithm for ODEs. a Using
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AdaGrad Explained
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Mathematics, Free Full-Text
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Gradient Method - an overview
![Online Gradient Descent – Parameter-free Learning and Optimization Algorithms](https://parameterfree.files.wordpress.com/2020/10/sgd_on_sin.png?w=640)
Almost Sure Convergence of SGD on Smooth Non-Convex Functions
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Gradient Descent Algorithm — a deep dive
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Electronics, Free Full-Text
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Gradient Descent Optimization Techniques.
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