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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RMSprop equation - dividing by a matrix?

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 ...
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What do we mean by “infrequent features”?

I am reading this blog post: https://ruder.io/optimizing-gradient-descent/index.html. In the section about AdaGrad, it says: It adapts the learning rate to the parameters, performing smaller updates (...
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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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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 ...