SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 151–160 of 3304 papers

TitleStatusHype
An Embedding is Worth a Thousand Noisy LabelsCode1
Enhanced MRI brain tumor detection and classification via topological data analysis and low-rank tensor decompositionCode1
An efficient aggregation method for the symbolic representation of temporal dataCode1
Estimating leverage scores via rank revealing methods and randomizationCode1
Explaining dimensionality reduction results using Shapley valuesCode1
A New Basis for Sparse Principal Component AnalysisCode1
Fast and Accurate Network Embeddings via Very Sparse Random ProjectionCode1
Fast conformational clustering of extensive molecular dynamics simulation dataCode1
Aha! Adaptive History-Driven Attack for Decision-Based Black-Box ModelsCode1
Correlation-based feature selection to identify functional dynamics in proteinsCode1
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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