SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

Showing 291300 of 3304 papers

TitleStatusHype
Dimensionality Reduction and (Bucket) Ranking: a Mass Transportation ApproachCode0
Dimensionality Reduction for Improving Out-of-Distribution Detection in Medical Image SegmentationCode0
ALPCAHUS: Subspace Clustering for Heteroscedastic DataCode0
ALPCAH: Subspace Learning for Sample-wise Heteroscedastic DataCode0
Dimensionality Collapse: Optimal Measurement Selection for Low-Error Infinite-Horizon ForecastingCode0
Weight Matrix Dimensionality Reduction in Deep Learning via Kronecker Multi-layer ArchitecturesCode0
Dimension-reduced Optimization of Multi-zone Thermostatically Controlled LoadsCode0
ALPCAH: Sample-wise Heteroscedastic PCA with Tail Singular Value RegularizationCode0
Adaptive Weighted Nonnegative Matrix Factorization for Robust Feature RepresentationCode0
Detecting covariate drift in text data using document embeddings and dimensionality reductionCode0
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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