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
Data-Driven Deep Learning to Design Pilot and Channel Estimator For Massive MIMO—0
GRASPEL: Graph Spectral Learning at Scale—0
Grassmann Averages for Scalable Robust PCA—0
Grassmann Graph Embedding—0
Efficient Estimation of the Central Mean Subspace via Smoothed Gradient Outer Products—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
Data-driven Model Predictive Control Method for DFIG-based Wind Farm to Provide Primary Frequency Regulation Service—0
Efficient Design of Hardware-Enabled Reservoir Computing in FPGAs—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