Instruct: Given the title of a paper, retrieve paper titles that are cited by the given paper.
Query: Limitations of the approximation capabilities of neural networks with one hidden layer
Multilayer feedforward networks with a nonpolynomial activation function can approximate any function
No bad local minima: Data independent training error guarantees for multilayer neural networks
Nearly-tight VC-dimension bounds for piecewise linear neural networks
On the Margin Theory of Feedforward Neural Networks
Intriguing properties of neural networks
a priori estimates of the generalization error for two - layer neural networks .
Low-Rank Approximations for Conditional Feedforward Computation in Deep Neural Networks
Interpreting Neural Networks With Nearest Neighbors
Theory of the Back Propagation Neural Network
DISCRETIZED NEURAL NETWORKS
Neural Tangent Kernel: Convergence and Generalization in Neural Networks
On the approximate realization of continuous mappings by neural networks
On the Computational Efficiency of Training Neural Networks
Sensitivity and Generalization in Neural Networks: an Empirical Study
Towards a Mathematical Understanding of the Difficulty in Learning with Feedforward Neural Networks
Artificial neural networks : fundamentals , computing , design , and application
A novel activation function for multilayer feed-forward neural networks
Deep, Narrow Sigmoid Belief Networks Are Universal Approximators
Overfitting and neural networks: conjugate gradient and backpropagation
Capabilities of threelayered perceptrons
A survey on classification techniques for opinion mining and sentiment analysis
Approximately Efficient Two-Sided Combinatorial Auctions
Disruptive technology: how Kodak missed the digital photography revolution
Malnutrition in the institutionalized elderly: the effects on wound healing.
Hinging hyperplanes for regression, classification, and function approximation