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 2841–2850 of 3304 papers

TitleStatusHype
State Representation Learning Using an Unbalanced AtlasCode0
Principal Orthogonal Latent Components Analysis (POLCA Net)Code0
Screening Sinkhorn Algorithm for Regularized Optimal TransportCode0
Visualization of High-dimensional Scalar Functions Using Principal ParameterizationsCode0
DeepNuParc: A Novel Deep Clustering Framework for Fine-scale Parcellation of Brain Nuclei Using Diffusion MRI TractographyCode0
Multivariate Functional Linear Discriminant Analysis for the Classification of Short Time Series with Missing DataCode0
Integrative Factorization of Bidimensionally Linked MatricesCode0
Secure Face Matching Using Fully Homomorphic EncryptionCode0
Multivariate Human Activity Segmentation: Systematic Benchmark with ClaSPCode0
Interactive Dimensionality Reduction for Comparative AnalysisCode0
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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