# Questions tagged [optimizers]

For questions about optimization methods/algorithms (also know as optimizers) in the context of machine learning and other AI subfields. Examples of optimizers are plain (stochastic) gradient descent, Adam, SGD with momentum, Adagrad, and RMSprop.

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### What is the formula for the momentum and Adam optimisers?

In the gradient descent algorithm, the formula to update the weight $w$, which has $g$ as the partial gradient of the loss function with respect to it, is: $$w\ -= r \times g$$ where $r$ is the ...
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### What kind of optimizer is suggested to use for binary classification of similar images?

I have spent some time searching Google and wasn't able to find out what kind of optimization algorithm is best for binary classification when images are similar to one another. I'd like to read ...
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I've been working on Neural Collaborative Filtering (NCF) recently to build a recommender system using Tensorflow Recommenders. Doing some hyperparameter tuning with different optimizers available in ...
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### What is uncentered variance and how it becomes equal to mean square in Adam?

I have been reading about Adam and AdamW (Here). The author mentioned that in "uncentered variance" we don't consider subtracting mean In this statement, the author is talking about ...
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### Joined vs Separate optimizer for Actor-Critic

Say that I have a simple Actor-Critic architecture, (I am not familiar with Tensorflow, but) in Pytorch we need to specify the parameters when defining an optimizer (SGD, Adam, etc) and therefore we ...
I've been trying to understand RMSprop for a long time, but there's something that keeps eluding me. $dW$ and $db$ are matrices (that's what I understand from the element-wise comment), so that must ...