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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 1631–1640 of 3304 papers

Title	Date	Tasks	Status	Hype
Distributed Principal Subspace Analysis for Partitioned Big Data: Algorithms, Analysis, and Implementation	Mar 11, 2021	Dimensionality Reduction	—Unverified	0
DefakeHop: A Light-Weight High-Performance Deepfake Detector	Mar 11, 2021	DeepFake DetectionDimensionality Reduction	CodeCode Available	1
Modern Dimension Reduction	Mar 11, 2021	Dimensionality Reduction	CodeCode Available	1
A Local Similarity-Preserving Framework for Nonlinear Dimensionality Reduction with Neural Networks	Mar 10, 2021	ClusteringDimensionality Reduction	—Unverified	0
BIKED: A Dataset for Computational Bicycle Design with Machine Learning Benchmarks	Mar 10, 2021	BIG-bench Machine LearningDesign Synthesis	CodeCode Available	1
Explaining dimensionality reduction results using Shapley values	Mar 9, 2021	ClusteringDimensionality Reduction	CodeCode Available	1
Simplicial Regularization	Mar 8, 2021	Data AugmentationDimensionality Reduction	CodeCode Available	0
Grassmann Graph Embedding	Mar 8, 2021	Dimensionality ReductionGraph Embedding	—Unverified	0
Empirical comparison between autoencoders and traditional dimensionality reduction methods	Mar 8, 2021	Dimensionality Reduction	—Unverified	0
Low-Rank Isomap Algorithm	Mar 6, 2021	ClusteringDimensionality 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