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_Suggestion for improvement:_
A port of [stochastic gradient based on Manopt](http://www.manopt.org/reference/manopt/solvers/stochasticgradient/stochasticgradient.html) would be useful for problems…
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https://liam.page/2019/06/18/OCD-needs-stochastic-gradient-descent/
作为一个强迫症（OCD）患者，曾经我一直对随机梯度下降（Stochastic Gradient Descent）表示怀疑。毕竟，每次只选择少量样本计算梯度，这靠谱吗？强迫症患者心里泛起了浓浓的怀疑。然而经年的实践经验结合理论分析表明，强迫症患者也需要随机梯度…
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# Stanford CS229 Lecture 2.Linear Regression and Gradient Descent - Just Do it
Outline Linear Regression Batch/Stochastic Gradient Descent Normal Equation
[https://temple17.github.io/cs229/le…
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Hi,
I am wondering about the meaning of "fine-tune" in the paper, page 41, Section I.2,
```
For CelebA, this means using a learning rate of 10−3
, a weight decay of 10−4
, a batch size of …
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@kangk9908
https://github.com/kcarnold/cs344-exam-23sp/blob/6a5024bc438f6db811ce74682ee7ba1fc4684112/u02-sa-learning-rate/SLO.md?plain=1#L1
From how I read the SLO from unit 2, I think it more rel…
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| Team Name | Affiliation |
|---|---|
| TheUnreasonableOne | None |
- Paper: [On the Computational Inefficiency of Large Batch Sizes for Stochastic Gradient Descent](https://openreview.net/pdf?i…
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Some questions and suggestions came to mind when I read about the gradient descent method:
- In section [Gradient Descent](https://ml-course.github.io/master/notebooks/02%20-%20Linear%20Models.html…
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## 🚀 Feature
I would like to suggest new stochastic optimizer additions to Pytorch.
### For non-convex loss functions
It is known that adaptive stochastic optimizers like Adam, Adagrad, RMSprop c…
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There is no example for Stochastic Gradient Descent in Chapter 8. I have tried to write one.
```
print("using minimize_stochastic_batch")
x = list(range(101))
y = [3*x_i + random.randint(-10,…
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Hi,
Are there any implementations where the scaled conjugate gradient (: SCG) method is used to optimize the model's hyperparameters, instead of LBFGS or the stochastic gradient descent?