MACHINE LEARNING FRAMEWORK FOR PRIORITIZING LOCATION MEASUREMENTS OF MULTIPLE DEVICES

Inventor(s)

Xu Zhang
Huy Tran
Matt Silverman
Abhishek Mukherji
Vinay Raghuram
Abhishek Bhattacharyya
Santosh Pandey

Abstract

Presented herein is a framework for prioritizing location measurements of multiple client devices. In particular, rather than using a round robin scheduling approach, the techniques presented herein utilize a machine learning block (e.g., random forests) to predict a score for each client device, along with a score-based scheduler.

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 License.

Recommended Citation

Zhang, Xu; Tran, Huy; Silverman, Matt; Mukherji, Abhishek; Raghuram, Vinay; Bhattacharyya, Abhishek; and Pandey, Santosh, "MACHINE LEARNING FRAMEWORK FOR PRIORITIZING LOCATION MEASUREMENTS OF MULTIPLE DEVICES", Technical Disclosure Commons, (December 21, 2018)
https://www.tdcommons.org/dpubs_series/1810