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 1471–1480 of 3304 papers

TitleStatusHype
Foundations of a Knee Joint Digital Twin from qMRI Biomarkers for Osteoarthritis and Knee Replacement—0
Anti-drift in electronic nose via dimensionality reduction: a discriminative subspace projection approach—0
Grassmann Averages for Scalable Robust PCA—0
Grassmann Graph Embedding—0
Forward-Cooperation-Backward (FCB) learning in a Multi-Encoding Uni-Decoding neural network architecture—0
Grassmannian Discriminant Maps (GDM) for Manifold Dimensionality Reduction with Application to Image Set Classification—0
Grassmannian Manifold Optimization Assisted Sparse Spectral Clustering—0
Grassmann Iterative Linear Discriminant Analysis with Proxy Matrix Optimization—0
Formation-Controlled Dimensionality Reduction—0
Concise Fuzzy Planar Embedding of Graphs: a Dimensionality Reduction Approach—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