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1. (WO2017176356) PARTITIONED MACHINE LEARNING ARCHITECTURE

Pub. No.:    WO/2017/176356    International Application No.:    PCT/US2017/016715
Publication Date: Fri Oct 13 01:59:59 CEST 2017 International Filing Date: Tue Feb 07 00:59:59 CET 2017
IPC: G06N 99/00
G06N 3/08
Applicants: WILLIAM MARSH RICE UNIVERSITY
Inventors: ROUHANI, Bita Darvish
MIRHOSEINI, Azalia
KOUSHANFAR, Farinaz
Title: PARTITIONED MACHINE LEARNING ARCHITECTURE
Abstract:
A system may include a processor and a memory. The memory may include program code that provides operations when executed by the processor. The operations may include: partitioning, based at least on a resource constraint of a platform, a global machine learning model into a plurality of local machine learning models; 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 of the plurality of local machine learning models.