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 read

In one paragraph

Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Fernando Hermosillo-ReynosoCenter for Research and Advanced Studies of the National Polytechnic Institute, Department of Electrical Engineering and Computer Sciences, Telecommunications Section, Av. del Bosque 1145, El Bajio, Zapopan 45019, Jalisco, Mexico.ORCID 0000-0002-6903-6509

Deni Torres-RomanCenter for Research and Advanced Studies of the National Polytechnic Institute, Department of Electrical Engineering and Computer Sciences, Telecommunications Section, Av. del Bosque 1145, El Bajio, Zapopan 45019, Jalisco, Mexico.ORCID 0000-0002-9813-7712

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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

Indexed as

Einstein productHadamard factor tensorsHadamard productmultitask learningmulti-view learningvehicle traffic surveillance

Identifiers

PMID39685998

DOI10.3390/s24237463

PMCPMC11644179

What OpenQuestion holds

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LicenceCC BY

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.