Is that true Newton's Method / Quasi Newton Method are not widely used in deep neutral network training?
14605
Why use gradient descent with neural networks?
59635
Stochastic gradient descent Vs Mini-batch size 1
99025
Actual impact of W=0 in a neural network
102350
Cost function of neural network is non-convex?
94250
Comprehensive list of activation functions in neural networks with pros/cons
84451
Role derivative of sigmoid function in neural networks
102544
Why should one use EM vs. say, Gradient Descent with MLE?
38690
Why are non zero-centered activation functions a problem in backpropagation?
88139
Why binary crossentropy can be used as the loss function in autoencoders?
100545
Number of nodes in hidden layers of neural network
102459
Why use gradient descent for linear regression, when a closed-form math solution is available?
13412
Motivating sigmoid output units in neural networks starting with unnormalized log probabilities linear in $z=w^Th+b$ and $\phi(z)$
92956
Is it possible to train a neural network without backpropagation?
98111
Sigmoid vs Relu function in Convnets
142667
Understanding how many biases are there in a neural network?
74626
Rate of convergence of Newton's method near a double root.
29512
Newtons Modified Method