SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 1271–1280 of 3304 papers

TitleStatusHype
Subspace Modeling for Fast Out-Of-Distribution and Anomaly Detection—0
Dimensionality Reduction and Wasserstein Stability for Kernel Regression—0
AUCO ResNet: an end-to-end network for Covid-19 pre-screening from cough and breathCode1
Sparse random hypergraphs: Non-backtracking spectra and community detectionCode0
Accelerating Plug-and-Play Image Reconstruction via Multi-Stage Sketched Gradients—0
Dimensionality Reduction and Prioritized Exploration for Policy Search—0
Bayesian Calibration for Activity Based Models—0
Diffusion Maps : Using the Semigroup Property for Parameter Tuning—0
Uniform Approximations for Randomized Hadamard Transforms with Applications—0
Vertical Federated Principal Component Analysis and Its Kernel Extension on Feature-wise Distributed DataCode1
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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