26 lines
858 B
Markdown
26 lines
858 B
Markdown
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---
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title: Updaters
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short_title: Updaters
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description: Special algorithms for gradient descent.
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category: Models
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weight: 10
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---
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## What are updaters?
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The main difference among the updaters is how they treat the learning rate. Stochastic Gradient Descent, the most common learning algorithm in deep learning, relies on `Theta` (the weights in hidden layers) and `alpha` (the learning rate). Different updaters help optimize the learning rate until the neural network converges on its most performant state.
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## Usage
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To use the updaters, pass a new class to the `updater()` method in either a `ComputationGraph` or `MultiLayerNetwork`.
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```java
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ComputationGraphConfiguration conf = new NeuralNetConfiguration.Builder()
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.updater(new Adam(0.01))
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// add your layers and hyperparameters below
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.build();
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```
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## Available updaters
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{{autogenerated}}
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