SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 561–570 of 3304 papers

TitleStatusHype
A GPU-Oriented Algorithm Design for Secant-Based Dimensionality Reduction—0
A Novel Filter Approach for Band Selection and Classification of Hyperspectral Remotely Sensed Images Using Normalized Mutual Information and Support Vector Machines—0
A novel extension of Generalized Low-Rank Approximation of Matrices based on multiple-pairs of transformations—0
Agnostically Learning Multi-index Models with Queries—0
A Convex Sparse PCA for Feature Analysis—0
Cognitive Coding of Speech—0
A Novel Denoising Technique and Deep Learning Based Hybrid Wind Speed Forecasting Model for Variable Terrain Conditions—0
A Novel Deep Clustering Framework for Fine-Scale Parcellation of Amygdala Using dMRI Tractography—0
Agile gesture recognition for capacitive sensing devices: adapting on-the-job—0
A Novel Bilingual Word Embedding Method for Lexical Translation Using Bilingual Sense Clique—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