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Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 3181–3190 of 3304 papers

Title	Date	Tasks	Status	Hype
Solving Large-Scale Sparse PCA to Certifiable (Near) Optimality	May 11, 2020	Dimensionality Reduction	CodeCode Available	0
Local manifold learning and its link to domain-based physics knowledge	Jul 1, 2022	BenchmarkingDimensionality Reduction	CodeCode Available	0
Solving NMF with smoothness and sparsity constraints using PALM	Oct 31, 2019	AstronomyClustering	CodeCode Available	0
Genomic data analysis in tree spaces	Jul 25, 2016	Dimensionality Reduction	CodeCode Available	0
A Linearly Convergent Algorithm for Distributed Principal Component Analysis	Jan 5, 2021	Dimensionality Reduction	CodeCode Available	0
An evaluation framework for dimensionality reduction through sectional curvature	Mar 17, 2023	Dimensionality Reduction	CodeCode Available	0
On the use of the Gram matrix for multivariate functional principal components analysis	Jun 22, 2023	Dimensionality Reduction	CodeCode Available	0
Long-term Conversation Analysis: Exploring Utility and Privacy	Jun 28, 2023	Action DetectionActivity Detection	CodeCode Available	0
Supervised Dimensionality Reduction for Big Data	Sep 5, 2017	Computational EfficiencyDimensionality Reduction	CodeCode Available	0
Analyzing scRNA-seq data by CCP-assisted UMAP and t-SNE	Jun 23, 2023	Dimensionality Reductionfeature selection	CodeCode Available	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