Automated Search for Configurations of Deep Neural Network Architectures

Understand

Deep Neural Networks (DNNs) are intensively used to solve a wide variety of complex problems.

• Although powerful, such systems require manual configuration and tuning.
• To this end, we view DNNs as configurable systems and propose an end-to-end framework that allows the configuration, evaluation and automated search for DNN architectures.
• Therefore, our contribution is threefold.