SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 2121–2130 of 3304 papers

TitleStatusHype
Inverting Nonlinear Dimensionality Reduction with Scale-Free Radial Basis Function Interpolation—0
Investigating Manifold Neighborhood size for Nonlinear Analysis of LIBS Amino Acid Spectra—0
involve-MI: Informative Planning with High-Dimensional Non-Parametric Beliefs—0
IRMAC: Interpretable Refined Motifs in Binary Classification for Smart Grid Applications—0
Is Deep Learning Network Necessary for Image Generation?—0
Isolation Kernel and Its Effect on SVM—0
Isometric Autoencoders—0
Isometric sketching of any set via the Restricted Isometry Property—0
Is 'Unsupervised Learning' a Misconceived Term?—0
Iterated Relevance Matrix Analysis (IRMA) for the identification of class-discriminative subspaces—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