SOTAVerified

Dimensionality Reduction

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

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Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1491–1500 of 3304 papers

TitleStatusHype
Forecasting Nonnegative Time Series via Sliding Mask Method (SMM) and Latent Clustered Forecast (LCF)—0
Hand Gesture Recognition with Leap Motion—0
Unsupervised Imputation of Non-ignorably Missing Data Using Importance-Weighted Autoencoders—0
Handling Overlapping Asymmetric Datasets -- A Twice Penalized P-Spline Approach—0
Concept Identification of Directly and Indirectly Related Mentions Referring to Groups of Persons—0
A Graphical Approach to State Variable Selection in Off-policy Learning—0
Forecastable Component Analysis (ForeCA)—0
Concept Drift Detection in Federated Networked Systems—0
HAVANA: Hierarchical stochastic neighbor embedding for Accelerated Video ANnotAtions—0
Flexible sampling of discrete data correlations without the marginal distributions—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