SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 971–980 of 3304 papers

TitleStatusHype
Is Deep Learning Network Necessary for Image Generation?—0
The Potential of Quantum Techniques for Stock Price Prediction—0
Free Lunch for Gait Recognition: A Novel Relation Descriptor—0
BERT4CTR: An Efficient Framework to Combine Pre-trained Language Model with Non-textual Features for CTR Prediction—0
An Empirical Study on Fault Detection and Root Cause Analysis of Indium Tin Oxide Electrodes by Processing S-parameter Patterns—0
Rigid Transformations for Stabilized Lower Dimensional Space to Support Subsurface Uncertainty Quantification and InterpretationCode0
Weighted Sparse Partial Least Squares for Joint Sample and Feature SelectionCode0
Gaussian Image Anomaly Detection with Greedy Eigencomponent Selection—0
Generative Models for Anomaly Detection and Design-Space Dimensionality Reduction in Shape Optimization—0
Deep Learning Architecture for Motor Imaged Words—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