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 3001–3010 of 3304 papers

TitleStatusHype
Cricket Player Profiling: Unraveling Strengths and Weaknesses Using Text Commentary Data—0
Cross-Sectional Dynamics Under Network Structure: Theory and Macroeconomic Applications—0
Cross-validation of matching correlation analysis by resampling matching weights—0
CSI Compression using Channel Charting—0
CUR Decompositions, Approximations, and Perturbations—0
DAC: Deep Autoencoder-based Clustering, a General Deep Learning Framework of Representation Learning—0
DA-Flow: Dual Attention Normalizing Flow for Skeleton-based Video Anomaly Detection—0
Data augmentation and feature selection for automatic model recommendation in computational physics—0
Data Augmentation For Label Enhancement—0
Data Dimension Reduction makes ML Algorithms efficient—0
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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