SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 1141–1150 of 3304 papers

TitleStatusHype
PAC-Bayesian Generalization Bounds for Adversarial Generative ModelsCode0
Novel Epileptic Seizure Detection Techniques and their Empirical Analysis—0
Linearized Wasserstein dimensionality reduction with approximation guarantees—0
Low-dimensional Data-based Surrogate Model of a Continuum-mechanical Musculoskeletal System Based on Non-intrusive Model Order Reduction—0
Mixed Multi-Model Semantic Interaction for Graph-based Narrative Visualizations—0
Sparse Dimensionality Reduction Revisited—0
Dimension Reduction and MARSCode0
Dimension reduction and redundancy removal through successive Schmidt decompositions—0
Monge, Bregman and Occam: Interpretable Optimal Transport in High-Dimensions with Feature-Sparse Maps—0
A Systematic Performance Analysis of Deep Perceptual Loss Networks: Breaking Transfer Learning ConventionsCode0
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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