Structured graph convolutional networks with stochastic masks for network embeddings

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United States of America

PATENT NO 11966832
APP PUB NO 20240046075A1
SERIAL NO

18264052

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Abstract

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A method includes receiving a first data set comprising embeddings of first and second types, generating a fixed adjacency matrix from the first dataset, and applying a first stochastic binary mask to the fixed adjacency matrix to obtain a first subgraph of the fixed adjacency matrix. The method also includes processing the first subgraph through a first layer of a graph convolutional network (GCN) to obtain a first embedding matrix, and applying a second stochastic binary mask to the fixed adjacency matrix to obtain a second subgraph of the fixed adjacency matrix. The method includes processing the first embedding matrix and the second subgraph through a second layer of the GCN to obtain a second embedding matrix, and then determining a plurality of gradients of a loss function, and modifying the first stochastic binary mask and the second stochastic binary mask using at least one of the plurality of gradients.

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  • VISA INTERNATIONAL SERVICE ASSOCIATION

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Inventor(s)

Inventor Name Address # of filed Patents Total Citations
Chen, Huiyuan San Jose, US 7 10
Lin, Yu-San Mountain View, US 13 14
Wang, Fei Fremont, US 1014 9284
Wang, Lan Urbana, US 188 1877
Yang, Hao San Jose, US 221 1810
Yeh, Michael Newark, US 24 108

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