Mini toolsDefinition
An adaptive learning rate optimization algorithm that divides the learning rate by an exponentially decaying average of squared gradients.
Detailed Explanation
RMSprop (Root Mean Square Propagation) maintains a moving average of squared gradients for each parameter and divides the learning rate by the square root of this average. This normalization helps prevent the learning rate from becoming too small when dealing with sparse gradients, addressing the vanishing gradient problem common in deep learning.
Use Cases
Deep neural network training, Recurrent neural network optimization, Online learning applications
