Engineering Commons^™

Efficient Neural Architecture Search With Multiobjective Evolutionary Optimization, Maria Gabriela Baldeón Calisto

USF Tampa Graduate Theses and Dissertations

Deep neural networks have become very successful at solving many complex tasks such as image classification, image segmentation, and speech recognition. These models are composed of multiple layers that have the capacity to learn increasingly higher-level features, without prior handcrafted specifications. However, the success of a deep neural network relies on finding the proper configuration for the task in hand. Given the vast number of hyperparameters and the massive search space, manually designing or fine-tuning deep learning architectures requires extensive knowledge, time, and computational resources.

There is a growing interest in developing methods that automatically design a neural network´s architecture, …