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Deep Learning for Computer Vision · End Term · 13 Sept 2026 · May 2026 term

Deep Learning for Computer Vision End Term 13 Sept 2026 — Question 22

Question 22

+3 marksOne or more correct options

Select all correct statements .

Select all that apply.

  1. A

    Backpropagation applies the chain rule efficiently through a computation graph.

  2. B

    Regularization can change the learned solution even when the network architecture is unchanged.

  3. C

    Gradient-descent variants can modify how current and past gradient information is used to update parameters.

  4. D

    Improving training means validation performance must increase after every individual parameter update.

Show answer

Correct answers

  • A

    Backpropagation applies the chain rule efficiently through a computation graph.

  • B

    Regularization can change the learned solution even when the network architecture is unchanged.

  • C

    Gradient-descent variants can modify how current and past gradient information is used to update parameters.

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Question 22 of 37 in the IIT Madras BS Deep Learning for Computer Vision (Deep Learning for Computer Vision) End Term paper sat on 13 Sept 2026, in the May 2026 term (Deep Learning For Computer Vision 13 Sep 26). It carries 3 marks.

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