SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

Showing 261270 of 3304 papers

TitleStatusHype
Analysis of Trade-offs in Fair Principal Component Analysis Based on Multi-objective OptimizationCode0
Weight Matrix Dimensionality Reduction in Deep Learning via Kronecker Multi-layer ArchitecturesCode0
Dimensionality Reduction and (Bucket) Ranking: a Mass Transportation ApproachCode0
Dimensionality Collapse: Optimal Measurement Selection for Low-Error Infinite-Horizon ForecastingCode0
Dimensionality Reduction for Binary Data through the Projection of Natural ParametersCode0
Dimensionality Reduction Meets Message Passing for Graph Node EmbeddingsCode0
Differentiable VQ-VAE's for Robust White Matter Streamline EncodingsCode0
Detecting covariate drift in text data using document embeddings and dimensionality reductionCode0
A more globally accurate dimensionality reduction method using tripletsCode0
DiffRed: Dimensionality Reduction guided by stable rankCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy90.9Unverified
2tSNEClassification Accuracy51.5Unverified
3IVISClassification Accuracy46.6Unverified
4UMAPClassification Accuracy41.3Unverified
#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy71.1Unverified
2QSClassification Accuracy68Unverified