17885144. MACHINE LEARNING (ML) DATA INPUT CONFIGURATION AND REPORTING simplified abstract (QUALCOMM Incorporated)
Contents
MACHINE LEARNING (ML) DATA INPUT CONFIGURATION AND REPORTING
Organization Name
Inventor(s)
Rajeev Kumar of San Diego CA (US)
Gavin Bernard Horn of La Jolla CA (US)
Xipeng Zhu of San Diego CA (US)
Shankar Krishnan of San Diego CA (US)
Aziz Gholmieh of Del Mar CA (US)
MACHINE LEARNING (ML) DATA INPUT CONFIGURATION AND REPORTING - A simplified explanation of the abstract
This abstract first appeared for US patent application 17885144 titled 'MACHINE LEARNING (ML) DATA INPUT CONFIGURATION AND REPORTING
Simplified Explanation
The abstract describes techniques for wireless communications by a User Equipment (UE) involving machine learning functions.
- UE receives a configuration for at least one machine learning function name (MLFN).
- UE receives machine learning (ML) data associated with the MLFN.
- UE uses the ML data as input for operation or training of an ML model associated with the MLFN.
---
- Potential Applications
- Wireless communication systems
- Machine learning applications in UE devices
- Problems Solved
- Enhancing wireless communication efficiency
- Improving machine learning capabilities in UE devices
- Benefits
- Increased performance in wireless communications
- Enhanced machine learning functionality in UE devices
Original Abstract Submitted
Certain aspects of the present disclosure provide techniques for wireless communications by a user equipment (UE). The UE receives a configuration for at least one machine learning function name (MLFN). The UE receives machine learning (ML) data associated with the at least one MLFN. The UE uses the ML data as an input for at least one of: operation or training of an ML model associated with the at least one MLFN.
