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 1951–1960 of 3304 papers

TitleStatusHype
Semi-supervised Embedding Learning for High-dimensional Bayesian OptimizationCode0
QEBA: Query-Efficient Boundary-Based Blackbox Attack—0
Physically interpretable machine learning algorithm on multidimensional non-linear fields—0
An Entropy Based Outlier Score and its Application to Novelty Detection for Road Infrastructure Images—0
Extração e Classificação de Características Radiômicas em Gliomas de Baixo Grau para Análise da Codeleção 1p/19q—0
Integrating LEO Satellite and UAV Relaying via Reinforcement Learning for Non-Terrestrial Networks—0
Triplet-Based Wireless Channel Charting: Architecture and Experiments—0
DartMinHash: Fast Sketching for Weighted SetsCode1
Rdimtools: An R package for Dimension Reduction and Intrinsic Dimension Estimation—0
Adversarial Canonical Correlation AnalysisCode0
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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