Invention Grant
- Patent Title: Transformer-based cross-node machine learning systems for wireless communication
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Application No.: US17452697Application Date: 2021-10-28
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Publication No.: US11871261B2Publication Date: 2024-01-09
- Inventor: June Namgoong , Yang Yang , Hyojin Lee , Taesang Yoo
- Applicant: QUALCOMM Incorporated
- Applicant Address: US CA San Diego
- Assignee: QUALCOMM Incorporated
- Current Assignee: QUALCOMM Incorporated
- Current Assignee Address: US CA San Diego
- Agency: QUALCOMM Incorporated
- Main IPC: H04W4/00
- IPC: H04W4/00 ; H04W24/10 ; H04B7/0456 ; H04L5/00 ; H04W72/23

Abstract:
Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may receive a transformer configuration that includes a transmitter neural network configured to be used to generate at least one latent vector corresponding to one or more computation tasks of a plurality of computation tasks associated with a transformer-based cross-node machine learning system. The UE may transmit the at least one latent vector based at least in part on instantiating the transmitter neural network. Numerous other aspects are described.
Public/Granted literature
- US20230136354A1 TRANSFORMER-BASED CROSS-NODE MACHINE LEARNING SYSTEMS FOR WIRELESS COMMUNICATION Public/Granted day:2023-05-04
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