Bo Hu

Title: Bo Hu and a Framework for Configuring Machine Learning Models.

Introduction

Bo Hu is an inventor associated with Gainesville, Florida, and the University of Florida Research Foundation Inc. His patent work addresses methods for configuring deep neural network machine learning models.

Latest Patents

Hu’s listed patent, “Configuration Process Framework for Machine Learning Models,” describes a method for configuring or training deep neural networks with hidden layers and an output layer. The approach configures hidden layers individually and sequentially, using a correlation measure between each layer’s output and a target signal. It adjusts layer parameters to maximize that measure, with the stated goals of improving computational efficiency and achieving optimality. Once configured on training data, the model can be used to perform automated tasks. Hu is credited with 1 patent.

Career Highlights

The available information identifies Hu’s patent contribution and his association with the University of Florida Research Foundation Inc. The invention focuses on a structured approach to training deep neural networks.

Collaborations

The patent is associated with the University of Florida Research Foundation Inc., indicating an institutional connection to the invention. No additional collaborators are specified in the provided information.

Conclusion

Bo Hu’s patent presents a layer-by-layer framework for configuring deep neural networks, emphasizing computational efficiency and optimized model training.