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 1411–1420 of 3304 papers

TitleStatusHype
Efficient Large-Scale Urban Parking Prediction: Graph Coarsening Based on Real-Time Parking Service Capability—0
Efficient Large-Scale Similarity Search Using Matrix Factorization—0
Generative Local Metric Learning for Nearest Neighbor Classification—0
Generative Modeling: A Review—0
Generative Modeling for Atmospheric Convection—0
Generative Models for Anomaly Detection and Design-Space Dimensionality Reduction in Shape Optimization—0
Generative Spatio-temporal GraphNet for Transonic Wing Pressure Distribution Forecasting—0
GENHOP: An Image Generation Method Based on Successive Subspace Learning—0
Covariance Matrix Adaptation Evolution Strategy Assisted by Principal Component Analysis—0
Bridging Dense and Sparse Maximum Inner Product Search—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