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 2391–2400 of 3304 papers

TitleStatusHype
Class Mean Vector Component and Discriminant Analysis—0
Graph Signal Representation with Wasserstein Barycenters—0
Classification of Cervical Cancer Dataset—0
Multi-Dimensional Scaling on Groups—0
Time Series Featurization via Topological Data Analysis—0
Combatting Adversarial Attacks through Denoising and Dimensionality Reduction: A Cascaded Autoencoder ApproachCode0
Use Dimensionality Reduction and SVM Methods to Increase the Penetration Rate of Computer Networks—0
SqueezeFit: Label-aware dimensionality reduction by semidefinite programmingCode0
Machine Learning of coarse-grained Molecular Dynamics Force Fields—0
Exploiting Wireless Channel State Information Structures Beyond Linear Correlations: A Deep Learning Approach—0
Show:102550
← PrevPage 240 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