SOTAVerified

Dimensionality Reduction

Dimensionality reduction is the task of reducing the dimensionality of a dataset.

( Image credit: openTSNE )

Papers

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Showing 681–690 of 3304 papers

TitleStatusHype
An Information Theoretic Feature Selection Framework for Big Data under Apache Spark—0
Contextual Categorization Enhancement through LLMs Latent-Space—0
Data-Driven Forecasting of High-Dimensional Transient and Stationary Processes via Space-Time Projection—0
Contrasting Syntagmatic and Paradigmatic Relations: Insights from Distributional Semantic Models—0
Contrastive analysis for scatterplot-based representations of dimensionality reduction—0
Contrastive inverse regression for dimension reduction—0
An information-geometric approach to feature extraction and moment reconstruction in dynamical systems—0
Application of Dictionary Learning in Alleviating Computational Burden of EEG Source Localization—0
Contrastive Multivariate Singular Spectrum Analysis—0
Cloud-based Deep Learning of Big EEG Data for Epileptic Seizure Prediction—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