query: Can we apply analyticity of a neural network to improve upon gradient descent?
positive_passages.docid: 61083
positive_passages.text: Why is Newton's method not widely used in machine learning?
negative_passages.docid: 91448
negative_passages.text: Should I normalize all data prior feeding the neural network models?
negative_passages.docid: 79882
negative_passages.text: Explanation of Spikes in training loss vs. iterations with Adam Optimizer
negative_passages.docid: 80182
negative_passages.text: Deriving the KL divergence loss for VAEs
negative_passages.docid: 58402
negative_passages.text: Importance of the bias node in neural networks
negative_passages.docid: 15759
negative_passages.text: Adding Regressors to Convolutional Neural Network
negative_passages.docid: 107608
negative_passages.text: Differentiation in support vector machine
negative_passages.docid: 123017
negative_passages.text: How does a back-propagation training algorithm work?
negative_passages.docid: 27266
negative_passages.text: XGBoost Loss function Approximation With Taylor Expansion
negative_passages.docid: 151892
negative_passages.text: How do you visualize neural network architectures?
negative_passages.docid: 16503
negative_passages.text: is there any diffrence to use nonlinear or liner activation function in single hidden layer network
negative_passages.docid: 157923
negative_passages.text: RMSProp Squared Gradients
negative_passages.docid: 68765
negative_passages.text: How do I make my neural network better at predicting sine waves?
negative_passages.docid: 112722
negative_passages.text: Can a neural network compute $y = x^2$?
negative_passages.docid: 63692
negative_passages.text: Is KNN a discriminative learning algorithm?
negative_passages.docid: 105631
negative_passages.text: Tensors in neural network literature: what's the simplest definition out there?
negative_passages.docid: 73225
negative_passages.text: local minima vs saddle points in deep learning