Improved Deep Learning Algorithm

Byung Joo Kim · JOURNAL OF ADVANCED INFORMATION TECHNOLOGY AND CONVERGENCE · 2018

Training a very large deep neural network can be painfully slow and prone to overfitting. Many researches have done for overcoming the problem. In this paper, a combination of early stopping and ADAM based deep neural network was presented. This form of deep network is useful for handling the big data because it automatically stop the training before overfitting occurs. Also generalization ability is better than pure deep neural network model.

Read the paper · More papers on PaperTik