What are the possible outcomes if we don’t do bias correction in ADAM?
The Algorithm will not converge to a local or global minima.
It would lead to initial updates that are much smaller.
It would lead to initial updates which are much larger.
Consider the assertion and the corresponding reason,
Assertion (A): The RMSProp Algorithm starts oscillating around the minima.
Reason (R): RMSProp is sensitive to initial learning rate value.
A is true but R is not the correct reason
A is True and R is the correct reason
A is False and therefore R
Suppose you have a deep neural network trained on a dataset with a small amount of labeled examples. After applying L2 regularization during training with a fixed value of regularization parameter, the following observations are made:
• The empirical error decreases significantly.
• The true error remains high.
• The variance of the error on different subsets of the training data is relatively low.
• When tested on a diverse set of unseen data, the model’s performance is inconsistent. Which of the following statements provides a plausible explanation for this scenario?
The model is underfitting due to excessive regularization.
L2 regularization effectively reduces both overfitting and underfitting.
The inconsistency in performance on unseen data is expected due to the limited labeled examples in the training set.
The model is still overfitting to the training data, and the regularization parameter needs adjustment.
Sign in with Google — it is free — to see every question with its answer and explanation, practise it in learning mode, or take it as a timed mock test.
The IIT Madras BS Deep Learning (Deep Learning) Quiz 2 paper sat on 24 Mar 2024, in the January 2024 term: 16 questions for 50 marks in 120 minutes. The first 3 questions are below. Sign in with Google — it is free — to see the whole paper with its answers and explanations, in learning mode or as a timed mock test.
| Feature | Deep Learning Quiz 2 24 Mar 2024 at a glance |
|---|---|
| Term | January 2024 term |
| Subject | Deep Learning |
| Course code | BSCS3004 |
| Questions | 16 |
| Marks | 50 |
| Duration | 120 min |
| MCQ | 7 |
| MSQ | 4 |
| Numerical | 5 |
| Official paper | IIT M DEGREE AN EXAM QDB2 24 Mar 2024 |
| Negative marking | No negative marking. |
| Updated |
