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 2331–2340 of 3304 papers

TitleStatusHype
MASS-UMAP: Fast and accurate analog ensemble search in weather radar archive—0
Mathematical Analysis on Out-of-Sample Extensions—0
Matrix Decomposition on Graphs: A Functional View—0
Matrix Factorization for Inferring Associations and Missing Links—0
Matrix Factorization in Tropical and Mixed Tropical-Linear Algebras—0
Matrix Normal PCA for Interpretable Dimension Reduction and Graphical Noise Modeling—0
Matrix Product Operator Restricted Boltzmann Machines—0
Maximally Correlated Principal Component Analysis—0
Maximum Covariance Unfolding : Manifold Learning for Bimodal Data—0
Maximum Covariance Unfolding Regression: A Novel Covariate-based Manifold Learning Approach for Point Cloud Data—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