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 2651–2660 of 3304 papers

TitleStatusHype
Simple strategies for recovering inner products from coarsely quantized random projections—0
Extreme Dimension Reduction for Handling Covariate Shift—0
Wisdom of the crowd from unsupervised dimension reduction—0
Robust Subspace Learning: Robust PCA, Robust Subspace Tracking, and Robust Subspace Recovery—0
Practical Hash Functions for Similarity Estimation and Dimensionality ReductionCode0
Random matrix approach to estimation of high-dimensional factor models—0
Universality of macroscopic neuronal dynamics in Caenorhabditis elegans—0
"I know it when I see it". Visualization and Intuitive Interpretability—0
Positive semi-definite embedding for dimensionality reduction and out-of-sample extensionsCode0
Deep Gaussian Mixture Models—0
Show:102550
← PrevPage 266 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