Abstract
Techniques are provided for associating similar devices and environments together so they can be effectively learned. Furthermore, a new device (e.g., smartphone) can be associated quickly with behaviors of other similar observed smartphones to avoid learning from scratch. Since wireless performance depends strongly on device and environments types, any machine learning method also needs to be conditioned on device and environment types.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Tan, Dan; Liston, Rob; Zhu, Xiaoqing; and Wildfeuer, Herb, "LEARNING ONE UNIVERSAL MACHINE LEARNING MODEL FOR WI-FI UNDER DIVERSE DEVICES AND ENVIRONMENTS", Technical Disclosure Commons, (November 14, 2018)
https://www.tdcommons.org/dpubs_series/1650