adagrad: AdaGrad SGD optimization
In ngme2: Linear Latent Non-Gaussian Models with Flexible Distributions
adagrad R Documentation
AdaGrad SGD optimization
Description
AdaGrad SGD optimization
Usage
adagrad(stepsize = 0.05, epsilon = 1e-08)
Arguments
stepsize
stepsize for SGD
epsilon
epsilon for numerical stability
Details
The update rule for AdaGrad is:
v_t = v_{t-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.
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| adagrad | R Documentation |
AdaGrad SGD optimization
Description
AdaGrad SGD optimization
Usage
adagrad(stepsize = 0.05, epsilon = 1e-08)
Arguments
stepsize |
stepsize for SGD |
epsilon |
epsilon for numerical stability |
Details
The update rule for AdaGrad is:
v_t = v_{t-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.
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