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 741–750 of 3304 papers

TitleStatusHype
Latent Dynamic Networked System Identification with High-Dimensional Networked Data—0
Statistical physics, Bayesian inference and neural information processing—0
On the Power of SVD in the Stochastic Block Model—0
Cluster Exploration using Informative Manifold ProjectionsCode0
Only 5\% Attention Is All You Need: Efficient Long-range Document-level Neural Machine Translation—0
Matrix Factorization in Tropical and Mixed Tropical-Linear Algebras—0
Robust Principal Component Analysis using Density Power Divergence—0
Elastic deep autoencoder for text embedding clustering by an improved graph regularization—0
CA-PCA: Manifold Dimension Estimation, Adapted for Curvature—0
Analysing race and sex bias in brain age prediction—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