SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 611–620 of 3304 papers

TitleStatusHype
Distance preserving model order reduction of graph-Laplacians and cluster analysis—0
A Functional approach for Two Way Dimension Reduction in Time Series—0
A Uniform Concentration Inequality for Kernel-Based Two-Sample Statistics—0
ClusTop: An unsupervised and integrated text clustering and topic extraction framework—0
C(NN)FD -- Deep Learning Modelling of Multi-Stage Axial Compressors Aerodynamics—0
Deep learning modelling of manufacturing and build variations on multi-stage axial compressors aerodynamics—0
An Investigation of Newton-Sketch and Subsampled Newton Methods—0
Cognitive Coding of Speech—0
Collaborative causal inference on distributed data—0
Clustering high dimensional meteorological scenarios: results and performance index—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