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Dimensionality Reduction

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

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Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 1231–1240 of 3304 papers

Title	Date	Tasks	Status	Hype
NeuroMapper: In-browser Visualizer for Neural Network Training	Oct 22, 2022	Dimensionality Reduction	CodeCode Available	0
Face Pyramid Vision Transformer	Oct 21, 2022	Dimensionality ReductionFace Recognition	CodeCode Available	0
An Experimental Study of Dimension Reduction Methods on Machine Learning Algorithms with Applications to Psychometrics	Oct 19, 2022	Dimensionality ReductionInterpretable Machine Learning	—Unverified	0
A Dashboard to Analysis and Synthesis of Dimensionality Reduction Methods in Remote Sensing	Oct 18, 2022	Dimensionality Reduction	—Unverified	0
Transformer-based dimensionality reduction	Oct 15, 2022	Data VisualizationDimensionality Reduction	—Unverified	0
Decentralized State Estimation In A Dimension-Reduced Linear Regression	Oct 13, 2022	Dimensionality Reductionregression	CodeCode Available	0
A Brief Survey on Representation Learning based Graph Dimensionality Reduction Techniques	Oct 13, 2022	Dimensionality ReductionGraph Representation Learning	—Unverified	0
Pinning control of networks: dimensionality reduction through simultaneous block-diagonalization of matrices	Oct 12, 2022	Dimensionality Reduction	—Unverified	0
Tackling Instance-Dependent Label Noise with Dynamic Distribution Calibration	Oct 11, 2022	Dimensionality Reduction	—Unverified	0
Efficient NTK using Dimensionality Reduction	Oct 10, 2022	Dimensionality Reduction	—Unverified	0

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All datasets MCA EMNIST

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	UDRN	Classification Accuracy	90.9	—	Unverified
2	tSNE	Classification Accuracy	51.5	—	Unverified
3	IVIS	Classification Accuracy	46.6	—	Unverified
4	UMAP	Classification Accuracy	41.3	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	UDRN	Classification Accuracy	71.1	—	Unverified
2	QS	Classification Accuracy	68	—	Unverified