Generalising Recursive Neural Models by Tensor Decomposition

Daniele Castellana
Daniele Castellana

IJCNN, pp. 1-8, 2020.

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Abstract:

Most machine learning models for structured data encode the structural knowledge of a node by leveraging simple aggregation functions (in neural models, typically a weighted sum) of the information in the node's neighbourhood. Nevertheless, the choice of simple context aggregation functions, such as the sum, can be widely sub-optimal. I...More

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