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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 2061–2070 of 3304 papers

Title	Date	Tasks	Status	Hype
Self Organizing Nebulous Growths for Robust and Incremental Data Visualization	Dec 9, 2019	Data VisualizationDimensionality Reduction	CodeCode Available	0
Control of ecological outcomes through deliberate parameter changes in a model of the gut microbiome	Dec 7, 2019	Dimensionality Reduction	CodeCode Available	0
Hybrid Kronecker Product Decomposition and Approximation	Dec 6, 2019	Dimensionality Reduction	—Unverified	0
Using Dimensionality Reduction to Optimize t-SNE	Dec 2, 2019	ClusteringDimensionality Reduction	CodeCode Available	0
On Distance and Kernel Measures of Conditional Independence	Dec 2, 2019	Causal DiscoveryDimensionality Reduction	—Unverified	0
Tight Dimensionality Reduction for Sketching Low Degree Polynomial Kernels	Dec 1, 2019	Dimensionality Reduction	—Unverified	0
Unsupervised Discovery of Temporal Structure in Noisy Data with Dynamical Components Analysis	Dec 1, 2019	Computational EfficiencyDimensionality Reduction	CodeCode Available	0
Precision-Recall Balanced Topic Modelling	Dec 1, 2019	Dimensionality ReductionInformation Retrieval	—Unverified	0
Dimensionality reduction: theoretical perspective on practical measures	Dec 1, 2019	BIG-bench Machine LearningDimensionality Reduction	—Unverified	0
Solving Interpretable Kernel Dimensionality Reduction	Dec 1, 2019	ClusteringDimensionality 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