SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 61–70 of 3304 papers

TitleStatusHype
Surrogate to Poincaré inequalities on manifolds for dimension reduction in nonlinear feature spaces—0
From Players to Champions: A Generalizable Machine Learning Approach for Match Outcome Prediction with Insights from the FIFA World Cup—0
Dimension-reduced Optimization of Multi-zone Thermostatically Controlled LoadsCode0
Optimization of embeddings storage for RAG systems using quantization and dimensionality reduction techniques—0
Recursive KL Divergence Optimization: A Dynamic Framework for Representation LearningCode1
GiBy: A Giant-Step Baby-Step Classifier For Anomaly Detection In Industrial Control Systems—0
PhyloProfile v2 -- Exploring multi-layered phylogenetic profiles at scaleCode1
A Novel Parameter-Tying Theorem in Multi-Model Adaptive Systems: Systematic Approach for Efficient Model Selection—0
Subject-independent Classification of Meditative State from the Resting State using EEG—0
A Multimodal Deep Learning Approach for White Matter Shape Prediction in Diffusion MRI Tractography—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