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
Oblivious subspace embeddings for compressed Tucker decompositions—0
Research on Early Warning Model of Cardiovascular Disease Based on Computer Deep Learning—0
Interpetable Target-Feature Aggregation for Multi-Task Learning based on Bias-Variance AnalysisCode0
Macroscopic Market Making Games via Multidimensional Decoupling Field—0
From Analog to Digital: Multi-Order Digital Joint Coding-Modulation for Semantic CommunicationCode1
Unsupervised learning of Data-driven Facial Expression Coding System (DFECS) using keypoint tracking—0
VERA: Generating Visual Explanations of Two-Dimensional Embeddings via Region AnnotationCode0
Enhancing Supervised Visualization through Autoencoder and Random Forest Proximities for Out-of-Sample Extension—0
Spherinator and HiPSter: Representation Learning for Unbiased Knowledge Discovery from SimulationsCode0
Noisy Data Visualization using Functional Data Analysis—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