IDiyas

For the Inventor, By the Inventor

Menlo Park, CA, United States of America

Rob Liston

USPTO Granted Patents = 11

Average Co-Inventor Count = 3.4

ph-index = 3

Forward Citations = 20(Granted Patents)


Company Filing History:

goldMedal11 out of 20,333 
 
Cisco Technology, Inc.
 patents

Years Active: 2017-2023

Loading Chart...
11 patents (USPTO):
1. 11699080 - Communication efficient machine learning of data across multiple sites (2023-07-11),
2. 11144616 - Training distributed machine learning with selective data transfers (2021-10-12),
3. 10937167 - Automated generation of pre-labeled training data (2021-03-02),
4. 10743188 - Wireless beamforming optimization using client location information (2020-08-11),
5. 10382973 - Wireless beamforming optimization using client location information (2019-08-13),
6. 10275683 - Clustering-based person re-identification (2019-04-30),
7. 10242449 - Automated generation of pre-labeled training data (2019-03-26),
8. 10234291 - Collaborative localization between phone and infrastructure (2019-03-19),
9. 10145962 - Adaptive localization and incremental deployment of infrastructure with crowd-sourced feedback (2018-12-04),
10. 9760517 - Network-USB (NUSB) communication system by which network applications communicate with USB devices over power-over-ethernet (PoE) connection (2017-09-12),
11. 9690732 - Power-over-ethernet (POE)-enabled network device and USB device power negotiation using USB to POE protocol conversion (2017-06-27),

Title: Rob Liston: Innovator in Machine Learning Technologies

Introduction

Rob Liston is a prominent inventor based in Menlo Park, CA. He has made significant contributions to the field of machine learning, holding a total of 11 patents. His work focuses on enhancing communication efficiency in distributed machine learning systems.

Latest Patents

One of Rob Liston's latest patents is titled "Communication Efficient Machine Learning of Data Across Multiple Sites." In this invention, a service receives machine learning-based generative models from various distributed sites. Each generative model is trained locally using unlabeled data to generate synthetic unlabeled data that mimics the original data. The service then trains a global machine learning model using both the labeled data from the sites and the synthetic data generated.

Another notable patent is "Training Distributed Machine Learning with Selective Data Transfers." This invention presents techniques for training a central machine learning model in a distributed system. It involves intelligently selecting a subset of data from local sites for transfer to the central site, allowing for effective training of the central model. The local training occurs at each site, with copies of the models sent to the central site for aggregation.

Career Highlights

Rob Liston is currently employed at Cisco Technology, Inc., where he continues to innovate in the field of machine learning. His work has been instrumental in advancing the capabilities of distributed systems and improving data communication efficiency.

Collaborations

Rob has collaborated with notable coworkers, including Xiaoqing Zhu and John George Apostolopoulos, contributing to various projects that enhance machine learning technologies.

Conclusion

Rob Liston's contributions to machine learning and his innovative patents reflect his expertise and commitment to advancing technology. His work continues to influence the field and drive progress in distributed 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…