SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 291–300 of 3304 papers

TitleStatusHype
Dimension-reduced Optimization of Multi-zone Thermostatically Controlled LoadsCode0
Optimization of embeddings storage for RAG systems using quantization and dimensionality reduction techniques—0
GiBy: A Giant-Step Baby-Step Classifier For Anomaly Detection In Industrial Control Systems—0
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
Unsupervised outlier detection to improve bird audio dataset labels—0
Interpretable non-linear dimensionality reduction using gaussian weighted linear transformationCode0
Learning Isometric Embeddings of Road Networks using Multidimensional Scaling—0
An Explainable Nature-Inspired Framework for Monkeypox Diagnosis: Xception Features Combined with NGBoost and African Vultures Optimization Algorithm—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