This inventor holds 1 USPTO granted patent and 1 published patent application. Top assignee: Google Inc.. Active years: 2026.
Company Filing History:
Years Active: 2026
Title: Ethan Jacob Leeman: Innovator in Machine Learning Privacy
Introduction
Ethan Jacob Leeman is a notable inventor based in Arlington, MA (US). He has made significant contributions to the field of machine learning, particularly in the area of privacy. His innovative approach to training machine-learned models has garnered attention in the tech community.
Latest Patents
Ethan holds a patent titled "Training machine-learned models with label differential privacy." This patent outlines a method for conducting differentially private communication of training data for machine learning. The process involves obtaining initial label data corresponding to feature data and determining a plurality of label bins to provide representative values for initial label values. The method generates noised label data based on a probability distribution over the label bins, ensuring privacy during the training of machine-learned models.
Career Highlights
Ethan is currently employed at Google Inc., where he continues to work on innovative projects that push the boundaries of technology. His expertise in machine learning and privacy has positioned him as a valuable asset to his team.
Collaborations
Ethan collaborates with Pritish Kamath, leveraging their combined knowledge and skills to advance their projects at Google Inc. Their partnership exemplifies the collaborative spirit that drives innovation in the tech industry.
Conclusion
Ethan Jacob Leeman is a pioneering inventor whose work in machine learning privacy is shaping the future of technology. His contributions are essential in ensuring that advancements in artificial intelligence are made with a focus on user privacy and data security.