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 441–450 of 3304 papers

TitleStatusHype
Approximate Grassmannian Intersections: Subspace-Valued Subspace Learning—0
Augment on Manifold: Mixup Regularization with UMAP—0
A Unified Framework for Optimization-Based Graph Coarsening—0
A Hybrid Data-Driven Approach For Analyzing And Predicting Inpatient Length Of Stay In Health Centre—0
A Unifying Family of Data-Adaptive Partitioning Algorithms—0
Auto-adaptative Laplacian Pyramids for High-dimensional Data Analysis—0
Auto-Detection of Safety Issues in Baby Products—0
A Deep Embedded Refined Clustering Approach for Breast Cancer Distinction based on DNA Methylation—0
Autoencoder Enhanced Realised GARCH on Volatility Forecasting—0
Active Linear Regression for _p Norms and Beyond—0
Show:102550
← PrevPage 45 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