SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 1541–1550 of 3304 papers

TitleStatusHype
On the Correspondence between Gaussian Processes and Geometric Harmonics—0
Classification of high-dimensional data with spiked covariance matrix structure—0
Efficient GPU implementation of randomized SVD and its applications—0
DenDrift: A Drift-Aware Algorithm for Host Profiling—0
Robust Linear Classification from Limited Training Data—0
Pharmacoprint -- a combination of pharmacophore fingerprint and artificial intelligence as a tool for computer-aided drug design—0
Dimension Reduction for Fréchet Regression—0
Visual Cluster Separation Using High-Dimensional Sharpened Dimensionality Reduction—0
Weight Vector Tuning and Asymptotic Analysis of Binary Linear Classifiers—0
Learning Stochastic Representations of Physical Systems—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