Assertion: gradient descent | /r/CapableOf | perform the parameters update
Facets:
value: of going through all examples
type: OTHER
value: on each example
type: LOCATION
value: for each observation
type: PURPOSE
Source sentences:
text: Instead of going through all examples, Stochastic Gradient Descent (SGD) performs the parameters update on each example (x^i,y^i).
text: Stochastic gradient descent (SGD) in contrast performs a parameter update for each training example \(x^{(i)}\) and label \(y^{(i)}\):
text: Stochastic gradient descent (SGD) performs parameter updates on each training example, whereas mini batch performs an update with n number of training examples in each batch.
text: Instead of going through all examples, Stochastic Gradient Descent (SGD) performs the parameters update on each example (x^i,y^i).
text: Instead of going through all examples, Stochastic Gradient Descent (SGD) performs the parameters update on each example (x^i,y^i).
text: Instead of going through all examples, Stochastic Gradient Descent (SGD) performs the parameters update on each example $(x^i,
text: Stochastic gradient descent (SGD) performs a parameter update for each observation.