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 721–730 of 3304 papers

TitleStatusHype
Low-Rank Robust Subspace Tensor Clustering for Metro Passenger Flow Modeling—0
Non-negative Subspace Feature Representation for Few-shot Learning in Medical Imaging—0
Human Activity Recognition using Smartphones—0
On the reduction of Linear Parameter-Varying State-Space models—0
Preventing Model Collapse in Gaussian Process Latent Variable ModelsCode0
Learning Intersections of Halfspaces with Distribution Shift: Improved Algorithms and SQ Lower Bounds—0
DMSSN: Distilled Mixed Spectral-Spatial Network for Hyperspectral Salient Object DetectionCode0
Comparison of Methods in Skin Pigment Decomposition—0
Enhancing Dimension-Reduced Scatter Plots with Class and Feature CentroidsCode0
Nonparametric Bellman Mappings for Reinforcement Learning: Application to Robust Adaptive Filtering—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