Freiburg, Germany

Frank Hutter

USPTO Granted Patents = 5 

 

Average Co-Inventor Count = 3.1

ph-index = 1

Forward Citations = 2(Granted Patents)


Company Filing History:


Years Active: 2023-2025

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5 patents (USPTO):Explore Patents

Title: Frank Hutter: Innovator in Machine Learning

Introduction

Frank Hutter is a prominent inventor based in Freiburg, Germany. He has made significant contributions to the field of machine learning, holding a total of five patents. His work focuses on enhancing the efficiency and effectiveness of machine learning algorithms.

Latest Patents

Hutter's latest patents include a "Method and device for transfer learning between modified tasks." This innovative method facilitates the transfer of hyperparameters from one machine learning algorithm to another. It involves creating a reduced search space and drawing candidate configurations from both the current and previous search spaces. The process utilizes a Tree Parzen Estimator (TPE) to optimize the drawing of candidate configurations, thereby improving the performance of the machine learning algorithm.

Another notable patent is the "Method and control device for generating training data for training a machine learning algorithm." This method generates additional training data from existing datasets by applying randomly selected augmentation functions. This approach enhances the training process of machine learning algorithms, making them more robust and effective.

Career Highlights

Frank Hutter is currently employed at Robert Bosch GmbH, where he continues to push the boundaries of machine learning research. His work has garnered attention for its practical applications and innovative methodologies.

Collaborations

Hutter collaborates with talented individuals in his field, including Samuel Gabriel Mueller and Lior Fuks. These partnerships contribute to the advancement of machine learning technologies and foster a collaborative research environment.

Conclusion

Frank Hutter is a key figure in the realm of machine learning, with a focus on innovative methods that enhance algorithm performance. His contributions through patents and collaborations continue to shape the future of this dynamic field.

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