Instruct: Given a scientific paper title, retrieve paper titles that are cited by the given paper.
Query: Experiments on Parallel Training of Deep Neural Network using Model Averaging
Parallel implementation of artificial neural network training
An Analysis of Deep Neural Network Models for Practical Applications
A Provably Efficient Algorithm for Training Deep Networks
Activation Ensembles for Deep Neural Networks
Averaging Weights Leads to Wider Optima and Better Generalization
Reinforced backpropagation for deep neural network learning
How Robust are Deep Neural Networks?
Weighted residuals for very deep networks
Rapid adaptation for deep neural networks through multi-task learning.
A Survey of Model Compression and Acceleration for Deep Neural Networks
A DAG Model of Synchronous Stochastic Gradient Descent in Distributed Deep Learning
Reinforced backpropagation improves test performance of deep networks: a toy-model study.
Parallel consensual neural networks
Learning to Optimize Neural Nets
Speeding up automatic hyperparameter optimization of deep neural networks by extrapolation of learning curves
Shakeout: A New Approach to Regularized Deep Neural Network Training
Neural Network Ensembles, Cross Validation, and Active Learning
Training Very Deep Networks
Accelerating recurrent neural network training using sequence bucketing and multi-GPU data parallelization
Annealed dropout training of deep networks
Improving Regressors using Boosting Techniques
Combining Long Short-Term Memory and Dynamic Bayesian Networks for Incremental Emotion-Sensitive Artificial Listening
Object tracking by mean shift and radial basis function neural networks
Exponential Family Harmoniums with an Application to Information Retrieval
Fuzzy rule-based systems for recognition-intensive classification in granular computing context