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 2341–2350 of 3304 papers

TitleStatusHype
License Plate Recognition with Compressive Sensing Based Feature Extraction—0
Principal Model Analysis Based on Partial Least Squares—0
Riemannian optimization with a preconditioning scheme on the generalized Stiefel manifold—0
Minimum description length as an objective function for non-negative matrix factorization—0
A Tangent Distance Preserving Dimensionality Reduction Algorithm—0
Higher-order Count Sketch: Dimensionality Reduction That Retains Efficient Tensor Operations—0
Distinguishing between Normal and Cancer Cells Using Autoencoder Node Saliency—0
Distributionally Robust and Multi-Objective Nonnegative Matrix Factorization—0
Throttling Malware Families in 2DCode0
A Deep Learning Framework for Assessing Physical Rehabilitation ExercisesCode0
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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