SOTAVerified

Dimensionality Reduction

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

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Papers

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Showing 2271–2280 of 3304 papers

TitleStatusHype
Local High-order Regularization on Data Manifolds—0
Locality and low-dimensions in the prediction of natural experience from fMRI—0
Locality preserving projection on SPD matrix Lie group: algorithm and analysis—0
Locality Preserving Projections for Grassmann manifold—0
Localized Sliced Inverse Regression—0
Localizing Persona Representations in LLMs—0
Locally Differentially Private Naive Bayes Classification—0
Locally Linear Embedding and fMRI feature selection in psychiatric classification—0
Locally Linear Unsupervised Feature Selection—0
Local Neighbor Propagation Embedding—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