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weight update vs weight update element

Both phrases are correct, but they are used in different contexts. 'Weight update' is a common term in machine learning and refers to the process of adjusting the weights in a neural network during training. 'Weight update element' could be used to refer to a specific component or aspect related to weight updates.

Last updated: March 21, 2024 • 515 views

weight update

This phrase is correct and commonly used in the context of machine learning and neural networks.

This term refers to the process of adjusting the weights in a neural network during training to improve the model's performance.

Examples:

  • The weight update step is crucial for the convergence of the neural network.
  • The algorithm uses a gradient descent method for weight update.
  • Back Propagation Weight Update Rule. This idea was first described by Werbos [ 3] and popularised by Rumelhart et al.[4]. Fig 1 A multilayer perceptron.
  • ... in the training set rather than waiting until all pairs in the training set have undergone these steps. Following image summarizes the weight update formula:.
  • The multiplicative weight update is our means of skewing the distribution. Denote the set of events/outcomes by P. We assume there is a matrix. M such that M(i, ...
  • May 1, 2012 ... the next round (hence the multiplicative weight update rule). Intuitively ... multiplicative weight update is our means of skewing the distribution.

Alternatives:

  • weight adjustment
  • weight modification
  • weight optimization
  • weight tuning
  • weight adaptation

weight update element

This phrase is correct and could be used to refer to a specific component or aspect related to weight updates.

This term could be used to specify a particular element or part within the process of weight updates, providing more detailed information.

Alternatives:

  • element of weight update
  • component of weight update
  • aspect of weight update
  • part of weight update
  • detail of weight update

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