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 2031–2040 of 3304 papers

TitleStatusHype
Hypoelliptic Diffusion Maps I: Tangent Bundles—0
Quantum-Classical Hybrid Machine Learning for Image Classification (ICCAD Special Session Paper)—0
I-Con: A Unifying Framework for Representation Learning—0
ICU Patient Deterioration prediction: a Data-Mining Approach—0
Identifying Chemicals Through Dimensionality Reduction—0
Identifying Dominant Industrial Sectors in Market States of the S&P 500 Financial Data—0
Identifying Feedforward and Feedback Controllable Subspaces of Neural Population Dynamics—0
Identifying Layers Susceptible to Adversarial Attacks—0
Identifying manifolds underlying group motion in Vicsek agents—0
Identifying semantic relations in a specialized corpus through distributional analysis of a cooccurrence tensor—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