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 921–930 of 3304 papers

TitleStatusHype
Dimensionality Reduction of Affine Variational Inequalities Using Random Projections—0
Automatic Double Reinforcement Learning in Semiparametric Markov Decision Processes with Applications to Long-Term Causal Inference—0
A Multi-view Dimensionality Reduction Algorithm Based on Smooth Representation Model—0
Dimensionality reduction methods for molecular simulations—0
Dimensionality Reduction in Sentence Transformer Vector Databases with Fast Fourier Transform—0
Automatic dimensionality reduction of Twin-in-the-Loop Observers—0
Dimensionality Reduction of Massive Sparse Datasets Using Coresets—0
Dimensionality Reduction of Movement Primitives in Parameter Space—0
A Deep Learning Approach with an Attention Mechanism for Automatic Sleep Stage Classification—0
Dimensionality Reduction in Deep Learning for Chest X-Ray Analysis of Lung Cancer—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