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 2001–2010 of 3304 papers

TitleStatusHype
Histograms of Sparse Codes for Object Detection—0
History Matching for Geological Carbon Storage using Data-Space Inversion with Spatio-Temporal Data Parameterization—0
Hodge Laplacians and Hodge Diffusion Maps—0
HOPS: High-order Polynomials with Self-supervised Dimension Reduction for Load Forecasting—0
Horizontal and Vertical Attention in Transformers—0
How Close Are the Eigenvectors of the Sample and Actual Covariance Matrices?—0
How Do Flow Matching Models Memorize and Generalize in Sample Data Subspaces?—0
How Do People Differ? A Social Media Approach—0
How to Use less Features and Reach Better Performance in Author Gender Identification—0
Human Activity Recognition using Smartphone—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