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 2261–2270 of 3304 papers

TitleStatusHype
Topological Stability: a New Algorithm for Selecting The Nearest Neighbors in Non-Linear Dimensionality Reduction Techniques—0
Topology Analysis of International Networks Based on Debates in the United Nations—0
Topology of cognitive maps—0
TopoMap++: A faster and more space efficient technique to compute projections with topological guarantees—0
Toward a unified theory of sparse dimensionality reduction in Euclidean space—0
A Diffusion Approximation Theory of Momentum SGD in Nonconvex Optimization—0
Toward Guaranteed Illumination Models for Non-Convex Objects—0
Towards a Dynamic Future with Adaptable Computing and Network Convergence (ACNC)—0
Towards a Fairer Non-negative Matrix Factorization—0
Towards a machine learning pipeline in reduced order modelling for inverse problems: neural networks for boundary parametrization, dimensionality reduction and solution manifold approximation—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