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1. (WO2018222900) COMPUTATIONALLY-EFFICIENT QUATERNION-BASED MACHINE-LEARNING SYSTEM

Pub. No.:    WO/2018/222900    International Application No.:    PCT/US2018/035439
Publication Date: Fri Dec 07 00:59:59 CET 2018 International Filing Date: Fri Jun 01 01:59:59 CEST 2018
IPC: G06N 3/04
G06N 99/00
Applicants: INTEL CORPORATION
MARTINEZ-CANALES, Monica Lucia
SINGH, Sudhir K.
SHARMA, Vinod
BHANDARU, Malini Krishnan
Inventors: MARTINEZ-CANALES, Monica Lucia
SINGH, Sudhir K.
SHARMA, Vinod
BHANDARU, Malini Krishnan
Title: COMPUTATIONALLY-EFFICIENT QUATERNION-BASED MACHINE-LEARNING SYSTEM
Abstract:
A quaternion deep neural network (QTDNN) includes a plurality of modular hidden layers, each comprising a set of QT computation sublayers, including a quaternion (QT) general matrix multiplication sublayer, a QT non-linear activations sublayer, and a QT sampling sublayer arranged along a forward signal propagation path. Each QT computation sublayer of the set has a plurality of QT computation engines. In each modular hidden layer, a steering sublayer precedes each of the QT computation sublayers along the forward signal propagation path. The steering sublayer directs a forward-propagating quaternion-valued signal to a selected at least one QT computation engine of a next QT computation subsequent sublayer.