SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1061–1070 of 3304 papers

TitleStatusHype
Diffusion Maps : Using the Semigroup Property for Parameter Tuning—0
Diffusion Maps meet Nyström—0
Audio Visual Speech Recognition using Deep Recurrent Neural Networks—0
A Characterization of the Non-Uniqueness of Nonnegative Matrix Factorizations—0
Diffusion map for clustering fMRI spatial maps extracted by independent component analysis—0
Diffusion Fingerprints—0
A Two-Stage Federated Learning Approach for Industrial Prognostics Using Large-Scale High-Dimensional Signals—0
Diffusion Component Analysis: Unraveling Functional Topology in Biological Networks—0
A Two-Stage Dual-Path Framework for Text Tampering Detection and Recognition—0
A Method for Classifying Snow Using Ski-Mounted Strain Sensors—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