CSE 5160 Machine Learning (Spring 2021) Assignment #4 (Due on April 23, 2021)

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Given a neural network, the structure is shown below. Each neuron in the neural network uses the logistic or sigmoid function () = !

!” $!” as activation function. %

[‘] is the output of the

linear part of )* neuron in layer ; % [‘] is the output of the activation part of )* neuron in layer .

 

 

 

 

 

 

 

1. [20 points] (Forward propagation) Given a training example (�⃗�, ), ∈ ℝ+, what is the

output of the neural network .?

 

2. [50 points] (Backpropagation) The loss function is defined by logistic loss function (.,) =

−[. + (1 − )(1 − .)] . Please derive the partial derivatives of loss function with

respect to parameters in the stochastic gradient descent update rules, that is, derive ,- ,.[$]

and

,- ,/[$]

, = 1,2,3.

 

! 0

+

….

…. ….

….

! [!] !

[!]

0 [!] 0

[!]

1 [!] 1

[!]

! [0] !

[0]

0 [0] 0

[0]

! [1] !

[1]

.