SOTAVerified

Dimensionality Reduction

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

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Papers

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Showing 1421–1430 of 3304 papers

TitleStatusHype
AgFlow: Fast Model Selection of Penalized PCA via Implicit Regularization Effects of Gradient Flow—0
T-SNE Is Not Optimized to Reveal Clusters in Data—0
Efficient GPU implementation of randomized SVD and its applications—0
On the Correspondence between Gaussian Processes and Geometric Harmonics—0
Classification of high-dimensional data with spiked covariance matrix structure—0
Robust Linear Classification from Limited Training Data—0
DenDrift: A Drift-Aware Algorithm for Host Profiling—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
Learning Compact Representations of Neural Networks using DiscriminAtive Masking (DAM)Code1
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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