US 11,818,806 B2
ML model training procedure
Rajeev Kumar, San Diego, CA (US); Eren Balevi, San Diego, CA (US); Taesang Yoo, San Diego, CA (US); Xipeng Zhu, San Diego, CA (US); Gavin Bernard Horn, La Jolla, CA (US); Shankar Krishnan, San Diego, CA (US); and Aziz Gholmieh, Del Mar, CA (US)
Assigned to QUALCOMM Incorporated, San Diego, CA (US)
Filed by QUALCOMM Incorporated, San Diego, CA (US)
Filed on May 18, 2021, as Appl. No. 17/323,242.
Prior Publication US 2022/0377844 A1, Nov. 24, 2022
Int. Cl. H04W 16/22 (2009.01); H04W 88/08 (2009.01); G06N 20/00 (2019.01); G06F 18/214 (2023.01)
CPC H04W 88/08 (2013.01) [G06F 18/214 (2023.01); G06N 20/00 (2019.01)] 30 Claims
OG exemplary drawing
 
1. An apparatus for wireless communication at a network entity, comprising:
memory; and
at least one processor coupled to the memory and configured to:
receive a trigger to activate a machine learning (ML) model training based on at least one of an indication from an ML model repository or a protocol of the network entity; and
transmit an ML model training request to activate the ML model training at one or more nodes.