IDiyas

For the Inventor, By the Inventor

Los Altos, CA, United States of America

Tal Shaked

USPTO Granted Patents = 16 

Average Co-Inventor Count = 5.1

ph-index = 6

Forward Citations = 106(Granted Patents)


Location History:

  • Mountain View, CA (US) (2015 - 2017)
  • Los Altos, CA (US) (2016 - 2023)

Company Filing History:

goldMedal16 out of 32,429 
 
Google Inc.
 patents

Years Active: 2015-2023

Loading Chart...
16 patents (USPTO):Explore Patents
1. 11663520 - Regularization relaxation scheme (2023-05-30),
2. 10762422 - Wide and deep machine learning models (2020-09-01),
3. 10713585 - Using template exploration for large-scale machine learning (2020-07-14),
4. 10509772 - Efficient locking of large data collections (2019-12-17),
5. 10438129 - Regularization relaxation scheme (2019-10-08),
6. 10102482 - Factorized models (2018-10-16),
7. 10062035 - Using variable length representations for machine learning statistics (2018-08-28),
8. 9805312 - Using an integerized representation for large-scale machine learning data (2017-10-31),
9. 9760595 - Parallel processing of data (2017-09-12),
10. 9569481 - Efficient locking of large data collections (2017-02-14),
11. 9536014 - Parallel processing of data (2017-01-03),
12. 9418343 - Multistage learner for efficiently boosting large datasets (2016-08-16),
13. 9390382 - Template regularization for generalization of learning systems (2016-07-12),
14. 9269057 - Using specialized workers to improve performance in machine learning (2016-02-23),
15. 9170848 - Parallel processing of data (2015-10-27),

Title: Tal Shaked: Innovator in Machine Learning

Introduction

Tal Shaked is a prominent inventor based in Los Altos, California. He has made significant contributions to the field of machine learning, holding a total of 16 patents. His work focuses on developing advanced methods and systems that enhance the capabilities of machine learning technologies.

Latest Patents

One of Tal Shaked's latest patents is the "Regularization relaxation scheme." This invention includes methods, systems, and apparatus for training machine learning systems. It involves receiving a plurality of training examples and training a machine learning system on each example to determine trained values for weights of a machine learning model. The training process includes assigning an initial value for a regularization penalty for a specific weight and adjusting this value during the training.

Another notable patent is the "Wide and deep machine learning models." This system comprises one or more computers and storage devices that implement a combined machine learning model. The model processes input with multiple features to generate a predicted output. It includes a deep machine learning model and a wide machine learning model, both trained jointly on training data to produce the final output.

Career Highlights

Tal Shaked is currently employed at Google Inc., where he continues to innovate in the field of machine learning. His work has been instrumental in advancing the capabilities of machine learning systems, making them more efficient and effective.

Collaborations

Throughout his career, Tal has collaborated with notable colleagues, including Tushar Deepak Chandra and Yoram Singer. These collaborations have contributed to the development of cutting-edge technologies in machine learning.

Conclusion

Tal Shaked is a key figure in the realm of machine learning, with a strong portfolio of patents that reflect his innovative spirit. His contributions are shaping the future of technology and enhancing the capabilities of machine learning systems.

This text is generated by artificial intelligence and may not be accurate.
Please report any incorrect information to support@idiyas.com
Loading…