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 301–310 of 3304 papers

TitleStatusHype
Accuracy and Privacy Evaluations of Collaborative Data Analysis—0
Approximate Matrix Multiplication with Application to Linear Embeddings—0
A Data Quarantine Model to Secure Data in Edge Computing—0
A Masked Pruning Approach for Dimensionality Reduction in Communication-Efficient Federated Learning Systems—0
Accelerating Vision Transformers Based on Heterogeneous Attention Patterns—0
A Machine-Learning-Aided Visual Analysis Workflow for Investigating Air Pollution Data—0
Alternative Channel Charting Techniques in Cellular Wireless Communications—0
A data-driven approach for multiscale elliptic PDEs with random coefficients based on intrinsic dimension reduction—0
Applying Supervised Learning Algorithms and a New Feature Selection Method to Predict Coronary Artery Disease—0
Alternating Diffusion Map Based Fusion of Multimodal Brain Connectivity Networks for IQ Prediction—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