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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 191–200 of 3304 papers

Title	Date	Tasks	Status	Hype
Less is more: Faster and better music version identification with embedding distillation	Oct 7, 2020	Dimensionality ReductionRetrieval	CodeCode Available	1
Level set learning with pseudo-reversible neural networks for nonlinear dimension reduction in function approximation	Dec 2, 2021	Dimensionality Reductionregression	CodeCode Available	1
Linear Recursive Feature Machines provably recover low-rank matrices	Jan 9, 2024	Dimensionality ReductionLow-Rank Matrix Completion	CodeCode Available	1
Locally Linear Embedding and its Variants: Tutorial and Survey	Nov 22, 2020	Dimensionality ReductionSurvey	CodeCode Available	1
Markov-Lipschitz Deep Learning	Jun 15, 2020	Deep LearningDimensionality Reduction	CodeCode Available	1
Metric Space Magnitude for Evaluating the Diversity of Latent Representations	Nov 27, 2023	Dimensionality ReductionDiversity	CodeCode Available	1
Minimum-Distortion Embedding	Mar 3, 2021	Dimensionality Reduction	CodeCode Available	1
Modern Dimension Reduction	Mar 11, 2021	Dimensionality Reduction	CodeCode Available	1
The Signature Kernel is the solution of a Goursat PDE	Jun 26, 2020	Dimensionality ReductionGPU	CodeCode Available	1
Distributional Principal Autoencoders	Apr 21, 2024	DecoderDimensionality Reduction	CodeCode Available	1

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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