SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

Showing 23812390 of 3304 papers

TitleStatusHype
A determinantal point process for column subset selection0
Dimensionality Reduction of Hyperspectral Imagery Based on Spatial-spectral Manifold Learning0
Random Projection in Deep Neural NetworksCode0
Nonlinear demixed component analysis for neural population data as a low-rank kernel regression problemCode0
Detecting the Trend in Musical Taste over the Decade -- A Novel Feature Extraction Algorithm to Classify Musical Content with Simple Features0
Deep Variational Sufficient Dimensionality Reduction0
Extending classical surrogate modelling to high-dimensions through supervised dimensionality reduction: a data-driven approach0
A Low Effort Approach to Structured CNN Design Using PCA0
Anti-drift in electronic nose via dimensionality reduction: a discriminative subspace projection approach0
A Tutorial on Distance Metric Learning: Mathematical Foundations, Algorithms, Experimental Analysis, Prospects and Challenges (with Appendices on Mathematical Background and Detailed Algorithms Explanation)0
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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