RMSprop
The centered version additionally maintains a moving average of the gradients, and uses that average to estimate the variance. Arguments Example Reference
RMSprop None Keras 3 API documentation Models API Layers API Callbacks API Ops API Optimizers SGD RMSprop Adam AdamW Adadelta Adagrad Adamax Adafactor Nadam Ftrl Lion Lamb Loss Scale Optimizer MultiOptimizer OptimizerMap Learning rate schedules API Muon Metrics Losses Data loading Tree API Built-in small datasets Keras Applications Mixed precision Multi-device distribution RNG API Quantizers Scope Rematerialization Utilities Keras 2 API documentation ► Keras 3 API documentation / Optimizers / RMSprop RMSprop [source] RMSprop class keras . optimizers . RMSprop ( learning_rate = 0.001 , rho = 0.
related reading
- RMSproppytorch.org
- Why Momentum Really Worksdistill.pub
- An overview of gradient descent optimization algorithmsruder.io
- Understanding Deep Learning Optimizers: Momentum, AdaGrad, RMSProp & Adam | Towards Data Sciencetowardsdatascience.com
- Deriving Muonjeremybernste.in
- A Visual Explanation of Gradient Descent Methods (Momentum, AdaGrad, RMSProp, Adam) | Towards Data Sciencetowardsdatascience.com
- Adampytorch.org
- SGDpytorch.org
- Muon: An optimizer for hidden layers in neural networks | Keller Jordan blogkellerjordan.github.io
- AdaGrad - Cornell University Computational Optimization Open Textbook - Optimization Wikioptimization.cbe.cornell.edu
- Stochastic gradient descent - Wikipediaen.m.wikipedia.org
- Proximal Policy Optimization - Spinning Up documentationspinningup.openai.com