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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 2441–2450 of 3304 papers

Title	Date	Tasks	Status	Hype	Score
Wisdom of the crowd from unsupervised dimension reduction	Nov 28, 2017	Decision MakingDimensionality Reduction	—Unverified	0	0
Word Embeddings as Features for Supervised Coreference Resolution	Sep 1, 2017	coreference-resolutionCoreference Resolution	—Unverified	0	0
Word Embeddings through Hellinger PCA	Apr 1, 2014	ChunkingDimensionality Reduction	—Unverified	0	0
Word Embedding Techniques for Classification of Star Ratings	Apr 18, 2025	ClassificationDimensionality Reduction	—Unverified	0	0
Word, graph and manifold embedding from Markov processes	Sep 18, 2015	Dimensionality ReductionWord Embeddings	—Unverified	0	0
Word Sense Disambiguation using Diffusion Kernel PCA	Jul 21, 2019	Dimensionality ReductionMachine Translation	—Unverified	0	0
Worst-Case Linear Discriminant Analysis	Dec 1, 2010	Dimensionality ReductionMetric Learning	—Unverified	0	0
Worst-Case Linear Discriminant Analysis as Scalable Semidefinite Feasibility Problems	Nov 27, 2014	Dimensionality ReductionGeneral Classification	—Unverified	0	0
XPCA: Extending PCA for a Combination of Discrete and Continuous Variables	Aug 22, 2018	Dimensionality Reduction	—Unverified	0	0
Xtreaming: an incremental multidimensional projection technique and its application to streaming data	Mar 8, 2020	Dimensionality Reduction	—Unverified	0	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