Instruct: Given a paper title, retrieve paper titles that are cited by the given paper
Query: Upper bounds on the number of hidden neurons in feedforward networks with arbitrary bounded nonlinear activation functions
Bounds on the number of hidden neurons in multilayer perceptrons
Bounds on the Approximation Power of Feedforward Neural Networks
Behaviour Analysis of Multilayer Perceptrons with Multiple Hidden Neurons and Hidden Layers
On the number of response regions of deep feed forward networks with piece-wise linear activations
A novel activation function for multilayer feed-forward neural networks
Classification ability of single hidden layer feedforward neural networks
Polynomial Bounds for VC Dimension of Sigmoidal and General Pfaffian Neural Networks
On the Margin Theory of Feedforward Neural Networks
Approximation capabilities of multilayer feedforward networks
Comparison of non-linear activation functions for deep neural networks on MNIST classification task
Approximation and estimation bounds for artificial neural networks
Learning the Number of Neurons in Deep Networks
Nearly-tight VC-dimension bounds for piecewise linear neural networks
LOBAL OPTIMALITY CONDITIONS FOR DEEP NEURAL NETWORKS
Layered Neural Networks with Gaussian Hidden Units as Universal Approximations
Understanding the difficulty of training deep feedforward neural networks
Complex backpropagation neural network using elementary transcendental activation functions
Towards a Mathematical Understanding of the Difficulty in Learning with Feedforward Neural Networks
Bounding and Counting Linear Regions of Deep Neural Networks
Nonlinear Neural Networks: Principles, Mechanisms, and Architectures
Line search algorithms with guaranteed sufficient decrease
Literature Survey on Door Lock Security Systems
Convolutional Neural Networks for So-Matching N-Grams in Ad-hoc Search Zhuyun Dai
The end of an era
Approximation by Superpositions of a Sigmoidal Function