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 1831–1840 of 3304 papers

TitleStatusHype
Dimensionality reduction, regularization, and generalization in overparameterized regressionsCode0
Gaussian Process Latent Variable Flows for Massively Missing Data—0
Manifold Partition Discriminant Analysis—0
Angular Embedding: A New Angular Robust Principal Component Analysis—0
Accelerating Text Mining Using Domain-Specific Stop Word Lists—0
Optimizing Offer Sets in Sub-Linear Time—0
Application of Computer Vision Techniques for Segregation of PlasticWaste based on Resin Identification Code—0
Strong and weak principles of neural dimension reduction—0
Functorial Manifold Learning—0
Interpretable Visualization and Higher-Order Dimension Reduction for ECoG DataCode0
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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