Events

Title:  Democratizing Deep Learning Development with DeepHyper Abstract:  In recent years, deep neural networks (DNNs) have achieved considerable success in learning complex nonlinear relationships between features and targets from large datasets. Nevertheless, designing high-performing DNN architecture for a given data set is an expert-driven, time-consuming, trial-and-error manual task. A major bottleneck in the construction of […]