Tensor Decompositions in Recursive NeuralNetworks for Tree-Structured Data

Daniele Castellana
Daniele Castellana
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Abstract:

The paper introduces two new aggregation functions to encode structural knowledge from tree-structured data. They leverage the Canonical and Tensor-Train decompositions to yield expressive context aggregation while limiting the number of model parameters. Finally, we define two novel neural recursive models for trees leveraging such agg...More

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