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 1141–1150 of 3304 papers

TitleStatusHype
Compressive Mahalanobis Metric Learning Adapts to Intrinsic Dimension—0
Defining Reference Sequences for Nocardia Species by Similarity and Clustering Analyses of 16S rRNA Gene Sequence Data—0
A survey of dimensionality reduction techniques based on random projection—0
A survey of dimensionality reduction techniques—0
Deep Variational Sufficient Dimensionality Reduction—0
Deep Variational Multivariate Information Bottleneck -- A Framework for Variational Losses—0
A Supervised Tensor Dimension Reduction-Based Prognostics Model for Applications with Incomplete Imaging Data—0
Deep Triphone Embedding Improves Phoneme Recognition—0
Deep topic modeling by multilayer bootstrap network and lasso—0
A Supervised Screening and Regularized Factor-Based Method for Time Series Forecasting—0
Show:102550
← PrevPage 115 of 331Next →
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