SOTAVerified

Dimensionality Reduction

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

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Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 3271–3280 of 3304 papers

TitleStatusHype
Optimal learning rates for Kernel Conjugate Gradient regression—0
Random Projections for k-means Clustering—0
Unsupervised Kernel Dimension Reduction—0
Efficient Optimization for Discriminative Latent Class Models—0
Generative Local Metric Learning for Nearest Neighbor Classification—0
Penalized Principal Component Regression on Graphs for Analysis of Subnetworks—0
Worst-Case Linear Discriminant Analysis—0
Inductive Regularized Learning of Kernel Functions—0
Robust PCA via Outlier PursuitCode0
Human Face Recognition using Line Features—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