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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 1041–1050 of 3304 papers

Title	Date	Tasks	Status	Hype
Interpretable Dimensionality Reduction by Feature Preserving Manifold Approximation and Projection	Nov 17, 2022	Dimensionality ReductionFeature Importance	—Unverified	0
Data Dimension Reduction makes ML Algorithms efficient	Nov 17, 2022	Dimensionality ReductionRepresentation Learning	—Unverified	0
RetroMAE v2: Duplex Masked Auto-Encoder For Pre-Training Retrieval-Oriented Language Models	Nov 16, 2022	Dimensionality ReductionInformation Retrieval	CodeCode Available	2
Topology of cognitive maps	Nov 16, 2022	Dimensionality ReductionHippocampus	—Unverified	0
Inverse Kernel Decomposition	Nov 11, 2022	Dimensionality Reduction	CodeCode Available	0
Minimalist Data Wrangling with Python	Nov 9, 2022	Dimensionality Reduction	CodeCode Available	1
Bridging Fairness and Environmental Sustainability in Natural Language Processing	Nov 8, 2022	Dimensionality ReductionFairness	—Unverified	0
Dimension Reduction for Efficient Data-Enabled Predictive Control	Nov 7, 2022	Dimensionality Reduction	—Unverified	0
Geodesic Sinkhorn for Fast and Accurate Optimal Transport on Manifolds	Nov 2, 2022	Dimensionality ReductionTime Series	—Unverified	0
Genomics Data Analysis via Spectral Shape and Topology	Nov 2, 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