SOTAVerified

Dimensionality Reduction

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

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Papers

Showing 141150 of 3304 papers

TitleStatusHype
A hyperparameter-tuning approach to automated inverse planningCode1
Binary Bleed: Fast Distributed and Parallel Method for Automatic Model SelectionCode1
Collection Space Navigator: An Interactive Visualization Interface for Multidimensional DatasetsCode1
The Signature Kernel is the solution of a Goursat PDECode1
Correlation-based feature selection to identify functional dynamics in proteinsCode1
Effective Sample Size, Dimensionality, and Generalization in Covariate Shift AdaptationCode1
DataLens: Scalable Privacy Preserving Training via Gradient Compression and AggregationCode1
Deep active subspaces - a scalable method for high-dimensional uncertainty propagationCode1
Deep Dimension Reduction for Supervised Representation LearningCode1
An Additive Autoencoder for Dimension EstimationCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy90.9Unverified
2tSNEClassification Accuracy51.5Unverified
3IVISClassification Accuracy46.6Unverified
4UMAPClassification Accuracy41.3Unverified
#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy71.1Unverified
2QSClassification Accuracy68Unverified