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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 2121–2130 of 3304 papers

Title	Date	Tasks	Status	Hype
Covariance-free Partial Least Squares: An Incremental Dimensionality Reduction Method	Oct 5, 2019	Computational EfficiencyDimensionality Reduction	CodeCode Available	0
A Comparison Study on Nonlinear Dimension Reduction Methods with Kernel Variations: Visualization, Optimization and Classification	Oct 4, 2019	ClassificationDimensionality Reduction	—Unverified	0
Fault Detection Using Nonlinear Low-Dimensional Representation of Sensor Data	Oct 2, 2019	Anomaly DetectionDimensionality Reduction	—Unverified	0
Near-Convex Archetypal Analysis	Oct 2, 2019	Dimensionality Reduction	—Unverified	0
Order-Preserving Wasserstein Discriminant Analysis	Oct 1, 2019	3D Action RecognitionAction Recognition	—Unverified	0
MASS-UMAP: Fast and accurate analog ensemble search in weather radar archive	Oct 1, 2019	Dimensionality ReductionRetrieval	—Unverified	0
TriMap: Large-scale Dimensionality Reduction Using Triplets	Oct 1, 2019	Dimensionality ReductionTriplet	CodeCode Available	0
Specializing Word Embeddings (for Parsing) by Information Bottleneck	Oct 1, 2019	Dimensionality ReductionPOS	CodeCode Available	0
A Quotient Space Formulation for Generative Statistical Analysis of Graphical Data	Sep 30, 2019	Dimensionality Reduction	CodeCode Available	0
Manifold Fitting in Ambient Space	Sep 30, 2019	Dimensionality 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