Elkton, MD, United States of America

Margaret A Payne

USPTO Granted Patents = 1 

Average Co-Inventor Count = 8.0

ph-index = 1

Forward Citations = 2(Granted Patents)


Company Filing History:


Years Active: 2023

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1 patent (USPTO):Explore Patents

Title: Innovations of Margaret A. Payne

Introduction

Margaret A. Payne is a notable inventor based in Elkton, MD (US). She has made significant contributions to the field of machine learning, particularly through her innovative patent. Her work focuses on automating functions on a graph structure, which has implications for various knowledge processing systems.

Latest Patents

Margaret A. Payne holds a patent for an "Unsupervised machine learning system to automate functions on a graph structure." This invention encompasses machine learning models, semantic networks, adaptive systems, artificial neural networks, convolutional neural networks, and other forms of knowledge processing systems. The ensemble machine learning system is integrated with a graph module that stores a graph structure, where entities and their relationships are represented as nodes and connection arcs. Additionally, a hotfile module and hotfile propagation engine work in conjunction with the graph module to implement various functionalities generated by the machine learning systems.

Career Highlights

Margaret is currently employed at Bank of America Corporation, where she applies her expertise in machine learning and graph structures. Her role allows her to contribute to innovative projects that leverage advanced technologies to improve banking functions and services.

Collaborations

Margaret has collaborated with notable colleagues, including Ronnie J. Morris and Dana M. Pusey-Conlin. These partnerships have fostered a creative environment that encourages the development of cutting-edge solutions in their respective fields.

Conclusion

Margaret A. Payne's contributions to machine learning and her innovative patent highlight her role as a significant inventor in the technology sector. Her work continues to influence advancements in knowledge processing systems and automation.

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