A comprehensive tutorial repository for learning deep learning model optimization techniques, including network tuning, backpropagation optimization, overfitting management, and root cause analysis.

We explore the use of large language models (LLMs) in hyperparameter optimization (HPO). By prompting LLMs with dataset and model descriptions, we develop a methodology where LLMs suggest ...

Abstract: As an emerging machine learning task, high-dimensional hyperparameter optimization (HO) aims at enhancing traditional deep learning models by simultaneously optimizing the neural networks’ ...

Abstract: The paper explores YOLO hyperparameter optimization crucial for robust deep learning models. It delves into optimizing parameters for three YOLO object detection categories: numeric, ...