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 1771–1780 of 3304 papers

TitleStatusHype
Application of Computer Vision Techniques for Segregation of PlasticWaste based on Resin Identification Code—0
Functorial Manifold Learning—0
Interpretable Visualization and Higher-Order Dimension Reduction for ECoG DataCode0
An efficient label-free analyte detection algorithm for time-resolved spectroscopy—0
TDAsweep: A Novel Dimensionality Reduction Method for Image Classification Tasks—0
Federated Learning System without Model Sharing through Integration of Dimensional Reduced Data Representations—0
Numerical Exploration of Training Loss Level-Sets in Deep Neural Networks—0
Binary Matrix Factorisation via Column Generation—0
Bayesian Nonparametric Dimensionality Reduction of Categorical Data for Predicting Severity of COVID-19 in Pregnant Women—0
Efficient Online Learning of Optimal Rankings: Dimensionality Reduction via Gradient DescentCode0
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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