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 1981–1990 of 3304 papers

TitleStatusHype
Dimensionality reduction via path integration for computing mRNA distributions—0
Supervised Visualization for Data Exploration—0
Sample complexity and effective dimension for regression on manifolds—0
Analysis of Trade-offs in Fair Principal Component Analysis Based on Multi-objective OptimizationCode0
Novelty Detection via Robust Variational AutoencodingCode0
Human brain activity for machine attention—0
An Augmented Translation Technique for low Resource language pair: Sanskrit to Hindi translation—0
Eigen-GNN: A Graph Structure Preserving Plug-in for GNNs—0
A Semiparametric Approach to Interpretable Machine Learning—0
Accelerated Search for Non-Negative Greedy Sparse Decomposition via Dimensionality Reduction—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