PARALLEL AND DISTRIBUTED PROCESSING OF PROPOSITIONAL LOGICAL NEURAL NETWORKS

An embodiment may include a processor that identifies a plurality of weights from the propositional logical neural network. The embodiment may convert the plurality of weights into a sparse matrix. The embodiment may convert a training set into a plurality of bound vectors. The embodiment may update...

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Bibliographic Details
Main Authors Choudhury, Anamitra Roy, Sabharwal, Yogish, Luus, Francois Pierre, Chakaravarthy, Venkatesan Thirumalai, Khan, Naweed Aghmad
Format Patent
LanguageEnglish
Published 30.11.2023
Subjects
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
PHYSICS
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Summary:An embodiment may include a processor that identifies a plurality of weights from the propositional logical neural network. The embodiment may convert the plurality of weights into a sparse matrix. The embodiment may convert a training set into a plurality of bound vectors. The embodiment may update the sparse matrix using a graphical processing unit (GPU). The embodiment may compute a loss parameter and based on determining the loss function is below threshold, update the plurality of weights of the propositional neural network.
Bibliography:Application Number: US202217804107