The cost function of a general neural network is defined as J(ŷ,y) 1 m L(VW), y() The loss function L(ỹ(¹), y() is defined by the logistic loss function L(¹),y) = [ylogy) + (1-y)log (1 - ¹)] Please list the stochastic gradient descent update rule, batch gradient descent update rule, and mini-batch gradient descent update rule. Explain the main difference of these three update rules.

The cost function of a general neural network is defined as J(ŷ,y) 1 m L(VW), y() The loss function L(ỹ(¹), y() is defined by the logistic loss function L(¹),y) = [ylogy) + (1-y)log (1 - ¹)] Please list the stochastic gradient descent update rule, batch gradient descent update rule, and mini-batch gradient descent update rule. Explain the main difference of these three update rules.

Operations Research : Applications and Algorithms

4th Edition

ISBN:9780534380588

Author:Wayne L. Winston

Publisher:Wayne L. Winston

Chapter20: Queuing Theory

Section20.4: The M/m/1/gd/∞/∞ Queuing System And The Queuing Formula L = Λw

Problem 14P

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