Port Chester, NY, United States of America

Christopher A Buchholz

This inventor holds 1 USPTO granted patent. Top assignee: International Business Machines Corporation. Active years: 2020.


% Patents Active = 100.0

Average Co-Inventor Count = 5.0

ph-index = 1

Forward Citations = 1(Granted Patents)


Company Filing History:


Years Active: 2020

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1 patent (USPTO):Explore Patents

Title: Christopher A Buchholz: Innovator in Machine Learning

Introduction

Christopher A Buchholz is a notable inventor based in Port Chester, NY (US). He has made significant contributions to the field of machine learning, particularly through his innovative patent. His work focuses on enhancing data processing techniques, which are crucial in today's data-driven world.

Latest Patents

Christopher A Buchholz holds a patent for a "Bayesian network based hybrid machine learning" system. This invention utilizes both labeled and unlabeled data to improve machine learning outcomes. For the unlabeled data, a fuzzy rules system assigns pseudo labels. A computer processes the labeled data using a first cognitive neural network and the pseudo-labeled data with a second cognitive neural network. The system then combines the results from both networks to produce outcomes. Additionally, the computer receives feedback on these outcomes and adjusts the parameters of the fuzzy rule system accordingly.

Career Highlights

Christopher is currently employed at International Business Machines Corporation, commonly known as IBM. His role at IBM allows him to work on cutting-edge technologies and contribute to advancements in machine learning and artificial intelligence.

Collaborations

Some of his notable coworkers include Elizabeth Bourgoin and Liyang Song. Their collaboration fosters a creative environment that enhances innovation and problem-solving within their projects.

Conclusion

Christopher A Buchholz is a pioneering inventor whose work in machine learning is shaping the future of data processing. His contributions, particularly through his patent, demonstrate the potential of hybrid systems in improving machine learning outcomes.

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