Analyzing weight distribution of neural networks

We investigate weight distribution of neural networks in order to understand and improve training process of neural networks. Generally, it takes a long time to train neural networks. However, when a new problem is presented, neural networks have to be trained again. No matter how many times neural networks have been trained before, the neural networks must be trained again without any benefit from the previous training process. The training process can be viewed as finding a solution point in the weight space. In this paper, we investigate the distribution of the solution points in the weight space to understand and speed up the training process