SOTAVerified

Dimensionality Reduction

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

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Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 331–340 of 3304 papers

TitleStatusHype
Accelerating hypersonic reentry simulations using deep learning-based hybridization (with guarantees)—0
A Robust Approach for Securing Audio Classification Against Adversarial Attacks—0
A selective review of sufficient dimension reduction for multivariate response regression—0
Accelerating hyperbolic t-SNE—0
Algorithms for Approximate Subtropical Matrix Factorization—0
2D+3D facial expression recognition via embedded tensor manifold regularization—0
Algorithmic Stability and Uniform Generalization—0
Algorithm-Agnostic Interpretations for Clustering—0
Adaptive Metric Dimensionality Reduction—0
A review of unsupervised learning in astronomy—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