2020/09/16 by Himanshu Pradeep Aswani, Aswani, Himanshu Pradeep, Amit Sethi +1
Computer Science · Mathematics · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #cs.LG #stat.ML
paper · pdf · doi:10.48550/arxiv.2009.07793
5 pages, 1 figure, 2 tables, pre-print
arxiv created 2020/09/16 · arxiv updated 2020/09/17
Current research suggests that the key factors in designing neural network architectures involve choosing number of filters for every convolution layer, number of hidden neurons for every fully connected layer, dropout and pruning. The default activation function in most cases is the ReLU, as it has empirically shown faster training convergence. We explore whether ReLU is the best choice if one is aiming to desire better modularity structure within a neural network.