A Tensor Space for Multi-View and Multitask Learning Based on Einstein and Hadamard Products: A Case Study on Vehicle Traffic Surveillance Systems
Fernando Hermosillo-Reynoso,
Deni Torres-Roman
Abstract:Since multi-view learning leverages complementary information from multiple feature sets to improve model performance, a tensor-based data fusion layer for neural networks, called Multi-View Data Tensor Fusion (MV-DTF), is used. It fuses M feature spaces X1,⋯,XM, referred to as views, in a new latent tensor space, S, of order P and dimension J1×⋯×JP, defined in the space of affine mappings composed of a multilinear map T:X1×⋯×XM→S—represented as the Einstein product between a (P+M)-order tensor A anda rank-one… Show more
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