Understanding Batch Normalization in Neural Networks
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Questions and Answers

What is the purpose of inducing a regularization term in the loss objective of a deep neural network?

  • To decrease regularization strength
  • To remove the regularization impact
  • To increase overfitting
  • To reduce the probability of overfitting (correct)
  • In a deep neural network, what does the hyperparameter λ represent in the regularized loss equation LΦ (θ) = LD (θ) + λΦ(θ)?

  • Learning rate
  • Training set
  • Optimization procedure
  • Regularization term (correct)
  • Which type of bias is used to tackle overfitting in deep neural networks by enforcing the learned mapping to take form in a constrained family?

  • Transductive bias
  • Inductive bias (correct)
  • Deductive bias
  • Conjunctive bias
  • What is the main benefit of using inductive bias to handle overfitting in deep neural networks?

    <p>Improving model generalization</p> Signup and view all the answers

    In the context of deep neural networks, what does the term 'Borel-measurable mapping' refer to?

    <p>Learnable mapping preserving certain properties</p> Signup and view all the answers

    How can dropout regularization help during the training of a deep neural network?

    <p>Mitigate overfitting</p> Signup and view all the answers

    What role does batch normalization play in deep learning models?

    <p>Improving convergence speed</p> Signup and view all the answers

    What happens to weights with certain characteristics when a regularization term is added to the loss objective of a deep neural network?

    <p>They become more attractive for optimization</p> Signup and view all the answers

    How does adding a regularization term to the loss objective affect the behavior of a deep neural network during training?

    <p>Stabilizes learning by discouraging extreme weight values</p> Signup and view all the answers

    What is the primary reason for using multiple channels in in-layer normalization methods for tensor values?

    <p>To exploit parallel processing capabilities</p> Signup and view all the answers

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