SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 2811–2820 of 3304 papers

TitleStatusHype
Maximally Correlated Principal Component Analysis—0
Cloud-based Deep Learning of Big EEG Data for Epileptic Seizure Prediction—0
RIPML: A Restricted Isometry Property based Approach to Multilabel Learning—0
Deep Gaussian Process for Crop Yield Prediction Based on Remote Sensing DataCode0
Stochastic Neighbor Embedding separates well-separated clusters—0
Toward the automated analysis of complex diseases in genome-wide association studies using genetic programmingCode0
Intrinsic Grassmann Averages for Online Linear, Robust and Nonlinear Subspace Learning—0
Representation of big data by dimension reduction—0
Computational Techniques in Multispectral Image Processing: Application to the Syriac Galen Palimpsest—0
Faster Discovery of Faster System Configurations with Spectral Learning—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