SOTAVerified

Dimensionality Reduction

Dimensionality reduction is the task of reducing the dimensionality of a dataset.

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Papers

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Showing 931–940 of 3304 papers

TitleStatusHype
Dimensionality Reduction on SPD Manifolds: The Emergence of Geometry-Aware Methods—0
Automatic dimensionality reduction of Twin-in-the-Loop Observers—0
A Deep Learning Approach with an Attention Mechanism for Automatic Sleep Stage Classification—0
Dimensionality reduction techniques to support insider trading detection—0
Dimensionality Reduction in Deep Learning for Chest X-Ray Analysis of Lung Cancer—0
Dimensionality Reduction has Quantifiable Imperfections: Two Geometric Bounds—0
Dimensionality Reduction using Elastic Measures—0
Dimensionality Reduction Using pseudo-Boolean polynomials For Cluster Analysis—0
Automatic Collection Creation and Recommendation—0
Dimensionality Reduction for Wasserstein Barycenter—0
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All datasetsMCAEMNIST

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy90.9—Unverified
2tSNEClassification Accuracy51.5—Unverified
3IVISClassification Accuracy46.6—Unverified
4UMAPClassification Accuracy41.3—Unverified
#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy71.1—Unverified
2QSClassification Accuracy68—Unverified