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 1841–1850 of 3304 papers

TitleStatusHype
Protecting Big Data Privacy Using Randomized Tensor Network Decomposition and Dispersed Tensor Computation—0
Prototype Discovery using Quality-Diversity—0
Improving Covariance-Regularized Discriminant Analysis for EHR-based Predictive Analytics of Diseases—0
Pseudo-Non-Linear Data Augmentation via Energy Minimization—0
PSF field learning based on Optimal Transport Distances—0
Puzzle Imaging: Using Large-scale Dimensionality Reduction Algorithms for Localization—0
QEBA: Query-Efficient Boundary-Based Blackbox Attack—0
Quantifying Context Overlap for Training Word Embeddings—0
Quantifying the Conceptual Error in Dimensionality Reduction—0
Quantization Algorithms for Random Fourier Features—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