Cupertino, CA, United States of America

Mitchel Weintraub


Average Co-Inventor Count = 2.3

ph-index = 5

Forward Citations = 626(Granted Patents)


Location History:

  • Fremont, CA (US) (2004)
  • Mountain View, CA (US) (2013 - 2015)
  • Cupertino, CA (US) (2007 - 2024)

Company Filing History:


Years Active: 2004-2024

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9 patents (USPTO):Explore Patents

Title: Mitchel Weintraub: Innovator in Exponential Modeling and Deep Learning

Introduction

Mitchel Weintraub is a prominent inventor based in Cupertino, CA (US). He has made significant contributions to the field of machine learning and deep learning, holding a total of 9 patents. His work focuses on enhancing the capabilities of machine-learned models through innovative approaches.

Latest Patents

One of Mitchel's latest patents involves exponential modeling with deep learning features. This patent enables humanly-specified relationships to contribute to a mapping that allows for the compression of the output structure of a machine-learned model. By leveraging a maximum entropy model, Mitchel's approach can utilize a machine-learned embedding to produce a classification output. This synergy between feature discovery capabilities of deep networks and human understanding of structural problems allows for the creation of compressed models. These models are particularly beneficial for 'on device' or resource-constrained scenarios, as they maintain accuracy while reducing complexity.

Career Highlights

Mitchel has worked with notable companies such as Google Inc. and Nuance Communications, Inc. His experience in these organizations has allowed him to refine his skills and contribute to groundbreaking innovations in the tech industry.

Collaborations

Throughout his career, Mitchel has collaborated with esteemed colleagues, including Francoise Beaufays and Brian Strope. These partnerships have further enriched his work and expanded the impact of his inventions.

Conclusion

Mitchel Weintraub stands out as an influential inventor in the realm of exponential modeling and deep learning. His innovative patents and collaborations reflect his commitment to advancing technology and improving machine learning applications.

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