Instruct: Given a scientific paper title, retrieve paper titles that are cited by the given paper
Query: Practical Gauss-Newton Optimisation for Deep Learning
Deep learning via Hessian-free optimization
Gradient Descent Finds Global Minima of Deep Neural Networks
Symmetry-invariant optimization in deep networks
Deep Learning without Poor Local Minima
N ov 2 01 8 Gradient Descent Finds Global Minima of Deep Neural Networks
Almost Global Convergence to Global Minima for Gradient Descent in Deep Linear Networks
Maximum Principle Based Algorithms for Deep Learning
A robust adaptive stochastic gradient method for deep learning
Deep Inverse Optimization
A Convergence Analysis of Gradient Descent for Deep Linear Neural Networks
Scalable Bayesian Optimization Using Deep Neural Networks
Reinforced backpropagation for deep neural network learning
Deep Frank-Wolfe For Neural Network Optimization
Learning Recurrent Neural Networks with Hessian-Free Optimization
Practical recommendations for gradient-based training of deep architectures
Improved Computation for Levenberg–Marquardt Training
Forward and Reverse Gradient-Based Hyperparameter Optimization
Regularization and Optimization strategies in Deep Convolutional Neural Network
Accelerating Deep Neural Network Training with Inconsistent Stochastic Gradient Descent
A Provably Efficient Algorithm for Training Deep Networks
Advanced traffic light control system using barrier gate and GSM
One weird trick for parallelizing convolutional neural networks
Reengineering the corporation: a manifesto for business revolution [Book Review]
Optical Detection of the Electromechanical Response of MEMS Micromirrors Designed for Scanning Picoprojectors
Exploring the Semantic Gap for Movie Recommendations