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gradient of the error function is vs gradient of the error function is computed

Both phrases are correct, but they serve different purposes. The first phrase is a concise statement, while the second phrase provides additional information on how the gradient is obtained. Depending on the context, you can choose the one that best fits your needs.

Last updated: March 19, 2024 • 520 views

gradient of the error function is

This phrase is correct and can be used to state the gradient of the error function.

This phrase is a concise way to refer to the gradient of the error function without specifying how it is computed.
  • error function. The network is initialized with randomly chosen weights. The gradient of the error function is computed and used to correct the initial weights.
  • 187 introduce a momentum term. The gradient of the error function is computed for each new combination of weights, but instead of just following the negative.
  • The gradient of the error function is. ∂e. ∂w. = 2(wTx)x − 2tx = −2(t − wTx)x . (34) . The weight vector is corrected by moving it in the opposite direction of the.
  • The gradient of the error function is the collection of partial derivatives of the error function with respect to the components of the parameter vector.

Alternatives:

  • gradient of the error function
  • error function gradient

gradient of the error function is computed

This phrase is correct and provides additional information on how the gradient is obtained.

This phrase is used when you want to specify that the gradient of the error function is being computed.
  • error function. The network is initialized with randomly chosen weights. The gradient of the error function is computed and used to correct the initial weights.
  • 187 introduce a momentum term. The gradient of the error function is computed for each new combination of weights, but instead of just following the negative.
  • gradient of the error function is computed by a finite element based sensitivity analysis scheme. The latter is enhanced by introducing the adjoint state vector ...
  • gradient of the error function is computed after the entire training has been presented to the entire network. Similarly, the training with the CG algorithm, ...

Alternatives:

  • computed gradient of the error function
  • gradient of the error function calculation

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