Tokyo, Japan

Masayoshi Mase

USPTO Granted Patents = 7 

 

Average Co-Inventor Count = 3.6

ph-index = 2

Forward Citations = 14(Granted Patents)


Location History:

  • Yokohama, JP (2015)
  • Tokyo, JP (2018 - 2023)

Company Filing History:


Years Active: 2015-2023

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7 patents (USPTO):

Title: Masayoshi Mase: Innovator in Computer Systems and Reinforcement Learning

Introduction

Masayoshi Mase is a prominent inventor based in Tokyo, Japan. He has made significant contributions to the field of computer systems and reinforcement learning, holding a total of seven patents. His work focuses on enhancing the efficiency and effectiveness of data evaluation and predictive modeling.

Latest Patents

Mase's latest patents include a computer system and method for presenting information related to the basis of predicted value output by a predictor. This innovative system outputs a predicted value of data to be evaluated using a predictor generated from learning data. The system comprises a predictor, an index calculation unit for calculating an interpretation index of the data, and an extraction unit that selects learning data useful for user interpretation of the predicted value. Additionally, he has developed a reward function generation method for calculating rewards in reinforcement learning. This method involves generating a reward function that includes multiple setting data related to key performance indicators, thereby enhancing the learning process.

Career Highlights

Throughout his career, Masayoshi Mase has worked with notable organizations such as Hitachi, Ltd. and Waseda University. His experience in these institutions has allowed him to refine his skills and contribute to groundbreaking advancements in technology.

Collaborations

Mase has collaborated with talented individuals in his field, including Yuxin Liang and Junji Yamamoto. These partnerships have fostered innovation and have been instrumental in the development of his patented technologies.

Conclusion

Masayoshi Mase's contributions to computer systems and reinforcement learning exemplify his dedication to innovation. His patents reflect a deep understanding of data evaluation and predictive modeling, making him a significant figure in the technology landscape.

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