SOTAVerified

Dimensionality Reduction

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

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Papers

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Showing 231–240 of 3304 papers

TitleStatusHype
Feature Clock: High-Dimensional Effects in Two-Dimensional Plots—0
A dimensionality reduction technique based on the Gromov-Wasserstein distance—0
A Dimensionality Reduction Method for Finding Least Favorable Priors with a Focus on Bregman Divergence—0
A cognitive based Intrusion detection system—0
An Impossibility Theorem for Node Embedding—0
3D Structural Phenotype of the Optic Nerve Head at the Intersection of Glaucoma and Myopia - A Key to Improving Glaucoma Diagnosis in Myopic Populations—0
A Dimensionality Reduction Approach for Convolutional Neural Networks—0
Visualization of AE's Training on Credit Card Transactions with Persistent Homology—0
A determinantal point process for column subset selection—0
An Algorithmic Information Calculus for Causal Discovery and Reprogramming Systems—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