This inventor holds 1 USPTO granted patent and 2 published patent applications. Top assignee: Nec Corporation. Active years: 2009.
Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile
Company Filing History:
Years Active: 2009
Title: Tsutomu Osoda: Innovator in Active Learning Systems
Introduction
Tsutomu Osoda is a prominent inventor based in Tokyo, Japan. He is known for his contributions to the field of active learning systems, which have significant implications in machine learning and data analysis. His innovative approach has led to the development of a unique patent that enhances the efficiency of learning algorithms.
Latest Patents
Tsutomu Osoda holds a patent for an "Active Learning Method and System." This invention involves an active learning system that samples known data and learns from it independently across multiple learning machines. The system intelligently selects data for further learning from unknown data. It includes a sampling weighting device that assigns weights to known data during sampling, a prediction weighting device that weighs the learning results from various machines, and a data weighting device that prioritizes learning results when selecting the next data to be learned. Notably, when there is a significant deviation in data counts, the weighting devices adjust to give more importance to the larger data sets. He has 1 patent to his name.
Career Highlights
Tsutomu Osoda is currently employed at NEC Corporation, where he continues to push the boundaries of technology and innovation. His work at NEC has allowed him to collaborate with other talented professionals in the field, further enhancing his contributions to active learning systems.
Collaborations
One of his notable coworkers is Yoshiko Yamashita. Together, they have worked on various projects that aim to improve machine learning techniques and applications.
Conclusion
Tsutomu Osoda's innovative work in active learning systems exemplifies the potential of technology to transform data analysis. His contributions are paving the way for advancements in machine learning, making him a significant figure in the field.
Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile
