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 2271–2280 of 3304 papers

TitleStatusHype
Unraveling the Veil of Subspace RIP Through Near-Isometry on Subspaces—0
CASS: Cross Adversarial Source Separation via Autoencoder—0
Fusion of heterogeneous bands and kernels in hyperspectral image processing—0
Multi-view Locality Low-rank Embedding for Dimension Reduction—0
Comparison of Machine Learning Models in Food Authentication Studies—0
Online Distributed Estimation of Principal Eigenspaces—0
EasiCS: the objective and fine-grained classification method of cervical spondylosis dysfunction—0
Dimensionality Reduction for Tukey Regression—0
Explore intrinsic geometry of sleep dynamics and predict sleep stage by unsupervised learning techniques—0
ForestDSH: A Universal Hash Design for Discrete Probability 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