SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 2491–2500 of 3304 papers

TitleStatusHype
Vehicles Lane-changing Behavior Detection—0
Supervised Kernel PCA For Longitudinal Data—0
Fourier analysis perspective for sufficient dimension reduction problem—0
A Projector-Based Approach to Quantifying Total and Excess Uncertainties for Sketched Linear Regression—0
DNN Feature Map Compression using Learned Representation over GF(2)Code0
Efficient Outlier Removal in Large Scale Global Structure-from-MotionCode0
Feature Dimensionality Reduction for Video Affect Classification: A Comparative Study—0
Low-complexity 8-point DCT Approximation Based on Angle Similarity for Image and Video Coding—0
Efficient Principal Subspace Projection of Streaming Data Through Fast Similarity Matching—0
Hybrid Subspace Learning for High-Dimensional Data—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