SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 1341–1350 of 3304 papers

TitleStatusHype
Fourier analysis perspective for sufficient dimension reduction problem—0
Fourier-Invertible Neural Encoder (FINE) for Homogeneous Flows—0
Fractal Descriptors of Texture Images Based on the Triangular Prism Dimension—0
FRANS: Automatic Feature Extraction for Time Series Forecasting—0
FRE: A Fast Method For Anomaly Detection And Segmentation—0
Fréchet Cumulative Covariance Net for Deep Nonlinear Sufficient Dimension Reduction with Random Objects—0
Free Lunch for Gait Recognition: A Novel Relation Descriptor—0
Frequency-dependent covariance reveals critical spatio-temporal patterns of synchronized activity in the human brain—0
Efficient Learning and Planning with Compressed Predictive States—0
Bridging Fairness and Environmental Sustainability in Natural Language Processing—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