SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 1571–1580 of 3304 papers

TitleStatusHype
Contextual Bandits with Sparse Data in Web setting—0
Ovarian Cancer Detection based on Dimensionality Reduction Techniques and Genetic Algorithm—0
Pseudocell Tracer—A method for inferring dynamic trajectories using scRNAseq and its application to B cells undergoing immunoglobulin class switch recombinationCode0
Automatic Collection Creation and Recommendation—0
Stochastic Mutual Information Gradient Estimation for Dimensionality Reduction NetworksCode0
Multi-view Clustering via Deep Matrix Factorization and Partition Alignment—0
Tensor Random Projection for Low Memory Dimension Reduction—0
Nonlinear Level Set Learning for Function Approximation on Sparse Data with Applications to Parametric Differential EquationsCode0
Photonic co-processors in HPC: using LightOn OPUs for Randomized Numerical Linear Algebra—0
Structured Sparse Non-negative Matrix Factorization with L20-Norm for scRNA-seq Data AnalysisCode0
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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