Regularization in Deep Learning is very important to overcome overfitting. When your training accuracy is very high, but test ...

Assuming that a smoothness condition and a suitable restriction on the structure of the regression function hold, it is shown that least squares estimates based on multilayer feedforward neural ...

Consistent Predictive Power The upper chart in Figure 2 shows performance improvements against the 15-day moving average, which we call historic model. The Adaptive Volume Model provides significant ...

Deep learning uses neural networks that have a large number of “hidden” layers to identify features. Hidden layers come between the input and output layers. The more layers in the model, the ...