SOTAVerified

Dimensionality Reduction

Dimensionality reduction is the task of reducing the dimensionality of a dataset.

( Image credit: openTSNE )

Papers

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Showing 981–990 of 3304 papers

TitleStatusHype
Capacity Analysis of Vector Symbolic Architectures—0
Online Kernel Sliced Inverse Regression—0
Federated Sufficient Dimension Reduction Through High-Dimensional Sparse Sliced Inverse Regression—0
Information loss from dimensionality reduction in 5D-Gaussian spectral data—0
Using Topological Data Analysis to classify Encrypted Bits—0
DR-WLC: Dimensionality Reduction cognition for object detection and pose estimation by Watching, Learning and CheckingCode0
Dual-sPLS: a family of Dual Sparse Partial Least Squares regressions for feature selection and prediction with tunable sparsity; evaluation on simulated and near-infrared (NIR) dataCode0
Segmenting thalamic nuclei from manifold projections of multi-contrast MRI—0
Fair and skill-diverse student group formation via constrained k-way graph partitioning—0
ImMesh: An Immediate LiDAR Localization and Meshing FrameworkCode2
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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