SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 3221–3230 of 3304 papers

TitleStatusHype
A Symmetric Rank-one Quasi Newton Method for Non-negative Matrix Factorization—0
Ensembles of Classifiers based on Dimensionality Reduction—0
Tensor Decompositions: A New Concept in Brain Data Analysis?—0
Inverting Nonlinear Dimensionality Reduction with Scale-Free Radial Basis Function Interpolation—0
Learning Densities Conditional on Many Interacting Features—0
Image Classification by Feature Dimension Reduction and Graph based Ranking—0
Bayesian Compressed Regression—0
Understanding Boltzmann Machine and Deep Learning via A Confident Information First Principle—0
Adaptive Metric Dimensionality Reduction—0
A Practical Algorithm for Topic Modeling with Provable GuaranteesCode0
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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