GATE DA 2026 Set 1 — Question 29
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Machine Learning → Neural Networks → Gradient Descent
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Question
Consider that for a supervised learning task, the objective function being minimized is , where is the input and is the parameter. Stochastic Gradient Descent with learning rate of 0.10 is used for parameter updates.Suppose that at the end of iteration , the value of becomes 10.00.Let be the input for iteration .The value of at the end of iteration is __________ . (Rounded off to two decimal places)
Correct answer
8.9 to 9.1
Solution
The objective function to be minimized is given by .The gradient of the objective function with respect to the parameter is:In Stochastic Gradient Descent (SGD), the parameter update rule is:where is the learning rate.Given:
- Learning rate
- Value of at the end of iteration (which is for iteration ):
- Input for iteration :
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