Company Filing History:
Years Active: 2024
Title: Marguerite Ellis: Innovator in Learning Machine Training
Introduction
Marguerite Ellis is a notable inventor based in San Francisco, CA. She has made significant contributions to the field of machine learning, particularly in the area of training systems that can distinguish between different types of plans. Her innovative approach has the potential to enhance the efficiency of learning machines in various applications.
Latest Patents
Marguerite Ellis holds a patent for a system titled "Learning machine training based on plan types." This invention involves a training database of reference metadata that describes various plans, including travel plans. The system trains a learning machine to differentiate between candidate first-type plans and candidate second-type plans. It utilizes decision trees generated from randomly selected subsets of reference metadata to improve the machine's classification capabilities. The trained machine is then modified based on asymmetrical penalties for incorrect classifications, ensuring a more accurate performance during run-time use.
Career Highlights
Marguerite is currently associated with Hipmunk Inc., where she applies her expertise in machine learning. Her work focuses on developing systems that enhance the functionality of learning machines, making them more adept at handling complex tasks. With her innovative mindset, she continues to push the boundaries of technology.
Collaborations
Marguerite collaborates with talented individuals such as Bharat Sri Vardhan Vemulapalli and Eric Etu. These partnerships foster a creative environment that encourages the exchange of ideas and the development of groundbreaking technologies.
Conclusion
Marguerite Ellis is a pioneering inventor whose work in learning machine training is shaping the future of technology. Her contributions are invaluable, and her innovative spirit continues to inspire others in the field.