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 2601–2610 of 3304 papers

TitleStatusHype
Angle constrained path to cluster multiple manifolds—0
Learning Integral Representations of Gaussian ProcessesCode0
Entropy-Isomap: Manifold Learning for High-dimensional Dynamic Processes—0
Out-of-sample extension of graph adjacency spectral embedding—0
First-order bifurcation detection for dynamic complex networks—0
Unsupervised vehicle recognition using incremental reseeding of acoustic signatures—0
Shamap: Shape-based Manifold Learning—0
Natural data structure extracted from neighborhood-similarity graphs—0
Fisherposes for Human Action Recognition Using Kinect Sensor DataCode0
A Diffusion Approximation Theory of Momentum SGD in Nonconvex Optimization—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