SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 1491–1500 of 3304 papers

TitleStatusHype
Low-complexity Rounded KLT Approximation for Image Compression—0
Generative Adversarial Networks and Adversarial Autoencoders: Tutorial and Survey—0
Dimension Reduction with Prior Information for Knowledge DiscoveryCode0
Model Reduction of Linear Dynamical Systems via Balancing for Bayesian InferenceCode0
An Attack on Facial Soft-biometric Privacy Enhancement—0
Machine Learning Based Forward Solver: An Automatic Framework in gprMaxCode0
The Diversity Metrics of Sub-models based on SVD of Jacobians for Ensembles Adversarial Robustness—0
Feature selection or extraction decision process for clustering using PCA and FRSD—0
Gaussian Determinantal Processes: a new model for directionality in data—0
MURAL: An Unsupervised Random Forest-Based Embedding for Electronic Health Record DataCode0
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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