Answers.Body: <p>Yes.</p>
  <p>A prominent class of &quot;gradient-free&quot; algorithms in ML world is known as <em>Evolution Strategies (ES)</em>. <a href="https://en.wikipedia.org/wiki/Evolutionary_computation" rel="nofollow noreferrer">Evolutionary Algorithms</a>, although existed for a long time, only a few have shown to scale well.</p>
  <p>Recently, the research group OpenAI managed to train Deep RL models with a specific variant of ES (with careful engineering). You can read <a href="https://openai.com/blog/evolution-strategies/" rel="nofollow noreferrer">this paper</a>. <a href="https://blog.otoro.net/2017/10/29/visual-evolution-strategies/" rel="nofollow noreferrer">This blog</a> by David Ha provides a starting point if you want to learn about ES and its modern derivatives.</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2021-08-18T15:35:10.090Z
Answers.LastActivityDate: 2021-08-18T15:35:10.090Z
Answers.UserDisplayName: ayandas
Body: <p>The only algorithm I know for updation of weights of a neural network is based on gradients. The update equation can be roughly written as</p>
  <p><span class="math-container">$$w \leftarrow w - \nabla_{w}L$$</span></p>
  <p>where <span class="math-container">$\nabla_{w}L$</span> is the gradient of loss function with respect to weights.</p>
  <p>Are there any learning algorithms for updating weights in neural networks that does not use gradients?</p>
  
Tags: <neural-networks><training><reference-request><stochastic-gradient-descent>
Title: Is there any way to train a neural network without using gradients?
UserDisplayName: hanugm
ThreadText: # Is there any way to train a neural network without using gradients?
  
  (Asked by: username_0 on 2021-08-18)
  
  The only algorithm I know for updation of weights of a neural network is based on gradients. The update equation can be roughly written as
  
  $$w \leftarrow w - \nabla\_{w}L$$
  
  where $\nabla\_{w}L$ is the gradient of loss function with respect to weights.
  
  Are there any learning algorithms for updating weights in neural networks that does not use gradients?
  
  **Tags:** neural-networks, training, reference-request, stochastic-gradient-descent
  
  ---
  
  ## 1 answers
  
  ### Answer by username_1 on 2021-08-18. Score: 4
  
  Yes.
  
  A prominent class of "gradient-free" algorithms in ML world is known as *Evolution Strategies (ES)*. [Evolutionary Algorithms](https://en.wikipedia.org/wiki/Evolutionary_computation), although existed for a long time, only a few have shown to scale well.
  
  Recently, the research group OpenAI managed to train Deep RL models with a specific variant of ES (with careful engineering). You can read [this paper](https://openai.com/blog/evolution-strategies/). [This blog](https://blog.otoro.net/2017/10/29/visual-evolution-strategies/) by David Ha provides a starting point if you want to learn about ES and its modern derivatives.
  
  
  ---
  
  