Patent ID: 11922313
Assignee: WILLIAM MARSH RICE UNIVERSITY
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 19:
20. A non-transitory computer-readable storage medium including program code, which when executed by at least one data processor, causes operations comprising:
partitioning, based at least on a resource constraint of a platform, a global machine learning model into a plurality of local machine learning models, each local machine learning model of the plurality of local machine learning models having a subset of a plurality of neurons and interconnections included in the global machine learning model, the global machine learning model being subjected to a depth first partitioning such that each local machine learning model of the plurality of local machine learning models include a same quantity of layers as the global machine learning models, and each local machine learning model of the plurality of local machine learning models having an output layer with a same quantity of neurons as an output layer of the global machine learning model;
transforming training data to at least conform to the resource constraint of the platform; and
training the global machine learning model by at least processing, at the platform, the transformed training data with a first local machine learning model of the plurality of local machine learning models, wherein training the global machine learning model further comprises updating a parameter of the global machine learning model based on at least one corresponding parameter from the plurality of local machine learning models after the transforming of training data.