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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 2151–2160 of 3304 papers

Title	Date	Tasks	Status	Hype	Score
Structured Feature Selection	Dec 1, 2015	Dimensionality Reductionfeature selection	—Unverified	0	0
Study on Downlink CSI compression: Are Neural Networks the Only Solution?	Feb 10, 2025	Dimensionality Reduction	—Unverified	0	0
Subject-independent Classification of Meditative State from the Resting State using EEG	Apr 25, 2025	Binary ClassificationClassification	—Unverified	0	0
Subspace approximation with outliers	Jun 30, 2020	Dimensionality Reduction	—Unverified	0	0
Subspace clustering of dimensionality-reduced data	Apr 27, 2014	ClusteringDimensionality Reduction	—Unverified	0	0
Subspace Embeddings for the Polynomial Kernel	Dec 1, 2014	Dimensionality Reduction	—Unverified	0	0
Subspace Modeling for Fast Out-Of-Distribution and Anomaly Detection	Mar 20, 2022	Anomaly DetectionCPU	—Unverified	0	0
Subspace Perspective on Canonical Correlation Analysis: Dimension Reduction and Minimax Rates	May 12, 2016	Dimensionality ReductionPrediction	—Unverified	0	0
Sufficient Dimension Reduction for Average Causal Effect Estimation	Sep 14, 2020	counterfactualDimensionality Reduction	—Unverified	0	0
0-dimensional Homology Preserving Dimensionality Reduction with TopoMap	Oct 10, 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