Assertion: neural network's parameter | /r/HasProperty | updated with adagrad
Facets:
value: according to its own gradient
type: OTHER
value: individually
type: MANNER
Source sentences:
text: With AdaGrad, each parameter is updated individually according to its own gradient, but with a new coefficient which attempts to equalize the learning rate between parameters which tend towards large gradients and those that tend to small ones.