rmsprop: Root Mean Square Propagation (RMSProp) SGD optimization
In ngme2: Linear Latent Non-Gaussian Models with Flexible Distributions
rmsprop R Documentation
Root Mean Square Propagation (RMSProp) SGD optimization
Description
Root Mean Square Propagation (RMSProp) SGD optimization
Usage
rmsprop(stepsize = 0.05, beta1 = 0.9, epsilon = 1e-08)
Arguments
stepsize
stepsize for SGD
beta1
beta1 for momentum
epsilon
epsilon for numerical stability
Details
The update rule for RMSProp is:
v_t = \beta_1 v_{t-1} + (1 - \beta_1) g_t^2
x_{t+1} = x_t - \text{stepsize} * \frac{g_t}{\sqrt{v_t} + \epsilon}
Value
a list of control variables for optimization
(used in control_opt function)
ngme2 documentation built on May 20, 2026, 9:10 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
| rmsprop | R Documentation |
Root Mean Square Propagation (RMSProp) SGD optimization
Description
Root Mean Square Propagation (RMSProp) SGD optimization
Usage
rmsprop(stepsize = 0.05, beta1 = 0.9, epsilon = 1e-08)
Arguments
stepsize |
stepsize for SGD |
beta1 |
beta1 for momentum |
epsilon |
epsilon for numerical stability |
Details
The update rule for RMSProp is:
v_t = \beta_1 v_{t-1} + (1 - \beta_1) g_t^2
x_{t+1} = x_t - \text{stepsize} * \frac{g_t}{\sqrt{v_t} + \epsilon}
Value
a list of control variables for optimization
(used in control_opt function)
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.