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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 2971–2980 of 3304 papers

Title	Date	Tasks	Status	Hype
A New Approach for Scalable Analysis of Microbial Communities	Dec 1, 2015	Dimensionality ReductionGeneral Classification	—Unverified	0
Structured Feature Selection	Dec 1, 2015	Dimensionality Reductionfeature selection	—Unverified	0
Implicit Sparse Code Hashing	Dec 1, 2015	Dimensionality Reduction	—Unverified	0
Space-Time Local Embeddings	Dec 1, 2015	Dimensionality Reduction	—Unverified	0
Algorithmic Stability and Uniform Generalization	Dec 1, 2015	Dimensionality ReductionLearning Theory	—Unverified	0
A fast, universal algorithm to learn parametric nonlinear embeddings	Dec 1, 2015	Dimensionality Reduction	—Unverified	0
Alternating Co-Quantization for Cross-Modal Hashing	Dec 1, 2015	Cross-Modal RetrievalDimensionality Reduction	—Unverified	0
Universality laws for randomized dimension reduction, with applications	Nov 30, 2015	compressed sensingDimensionality Reduction	—Unverified	0
A Normative Theory of Adaptive Dimensionality Reduction in Neural Networks	Nov 30, 2015	Dimensionality Reduction	—Unverified	0
Binding constants of membrane-anchored receptors and ligands: a general theory corroborated by Monte Carlo simulations	Nov 24, 2015	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