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Indian Institute of Technology Kharagpur
Deep Learning
Assignment- Week 7
TYPE OF QUESTION: MCQ/MSQ
Number of questions: 10 Total mark: 10 X 1 = 10
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QUESTION 1:
Select the correct option about Sparse Autoencoder?
Statement 1: Sparse autoencoders introduces information bottleneck by reducing the number
of nodes at hidden layers
Statement 2: The idea is to encourage network to learn an encoding and decoding which only
relies on activating a small number of neurons
a. Both the statements are true
b. Statement 1 is true, but Statement 2 is false
c. Statement 1 is false, but statement 2 is true
d. Both the statements are false
Correct Answer: c
Detailed Solution:
Sparse autoencoders introduces an information bottleneck without requiring a reduction in
the number of nodes at hidden layers. It encourages network to learn an encoding and
decoding which only relies on activating a small number of neurons.
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QUESTION 2:
Select the correct option about Denoising autoencoders?
Statement A: The loss is between the original input and the reconstruction from a noisy version
of the input
Statement B: Denoising autoencoders can be used as a tool for feature extraction.
a. Both the statements are false
b. Statement A is false but Statement B is true
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Indian Institute of Technology Kharagpur
c. Statement A is true but Statement B is false
d. Both the statements are true
Correct Answer: d
Detailed Solution:
For denoising autoencoder, both statement 1 and 2 are true. Thus option (d) is correct
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QUESTION 3:
Which of the following autoencoder methods uses corrupted versions of the input?
a. Overcomplete design
b. Undercomplete Design
c. Sparse Design
d. Denoising Design
Correct Answer: d
Detailed Solution:
Refer to classroom lecture.
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QUESTION 4:
Which of the following autoencoder methods uses a hidden layer with fewer units than the
input layer?
a. Overcomplete design
b. Undercomplete Design
c. Sparse Design
d. Denoising Design
Correct Answer: b
Detailed Solution:
Refer to classroom lecture.
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Indian Institute of Technology Kharagpur
QUESTION 5:
Which of the following is false about autoencoder?
a. Autoencoders possesses generalization capabilities
b. Autoencoders are best suited for image captioning task
c. Its objective is to minimize the reconstruction loss so that output is similar to
input
d. It compresses the input into a latent space representation and then reconstruct
the output from it
Correct Answer: b
Detailed Solution:
Except option (b), rest all the options are true about auroencoders
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QUESTION 6:
Find the value of ; being the delta function and * being the
convolution operation.
a.
b.
c.
d.
Correct Answer: c
Detailed Solution:
Convolution of a function with delta shifts accordingly
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QUESTION 7:
Impulse response is the output of ________________system due to impulse input applied at
time=0. Fill in the blanks from the options below.
a. Linear
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Indian Institute of Technology Kharagpur
b. Time Varying
c. Time Invariant
d. Linear And Time Invariant
Correct Answer: d
Detailed Solution:
Impulse response is output of LTI system due to impulse input pplied at time t=0 or n=0.
Behaviour of an LTI system is characterized by its impulse response.
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QUESTION 8:
The impulse function is ___ when t=0. Fill in the blanks.
a. 1
b. 0
c. Infinity
d. None of the above
Correct Answer: a
Detailed Solution:
Self-explainable from the definition of impulse function
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QUESTION 9:
Given the image below where, Row 1: Original Input, Row 2: Noisy input, Row 3: Reconstructed
output. Choose one of the following variants of autoencoder that is most suited to get Row 3
from Row 2.
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Indian Institute of Technology Kharagpur
a. Stacked autoencoder
b. Sparse autoencoder
c. Denoising autoencoder
d. None of the above
Correct Answer: c
Detailed Solution:
Reconstruction of original noise-free data from noisy input is the tasks of denoising
autoencoder
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QUESTION 10:
Which of the following is true for Contractive Autoencoders?
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Indian Institute of Technology Kharagpur
a. penalizing instances where a small change in the input leads to a large change in
the encoding space
b. penalizing instances where a large change in the input leads to a small change in
the encoding space
c. penalizing instances where a small change in the input leads to a small change in
the encoding space
d. None of the above
Correct Answer: a
Detailed Solution:
Direct from definition of Contractive autoencoders
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