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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 2671–2680 of 3304 papers

Title	Date	Tasks	Status	Hype
Inversion using a new low-dimensional representation of complex binary geological media based on a deep neural network	Oct 25, 2017	Dimensionality Reduction	—Unverified	0
DPCA: Dimensionality Reduction for Discriminative Analytics of Multiple Large-Scale Datasets	Oct 25, 2017	Dimensionality Reduction	—Unverified	0
Bayesian Inference over the Stiefel Manifold via the Givens Representation	Oct 25, 2017	Bayesian InferenceDimensionality Reduction	—Unverified	0
SMSSVD - SubMatrix Selection Singular Value Decomposition	Oct 23, 2017	Dimensionality Reduction	CodeCode Available	0
Elliptical modeling and pattern analysis for perturbation models and classfication	Oct 22, 2017	blind source separationDimensionality Reduction	—Unverified	0
Deep Triphone Embedding Improves Phoneme Recognition	Oct 22, 2017	Dimensionality ReductionGeneral Classification	—Unverified	0
Learning Wasserstein Embeddings	Oct 20, 2017	DecoderDimensionality Reduction	CodeCode Available	1
Nonlinear Supervised Dimensionality Reduction via Smooth Regular Embeddings	Oct 19, 2017	Dimensionality ReductionSupervised dimensionality reduction	—Unverified	0
S-Isomap++: Multi Manifold Learning from Streaming Data	Oct 17, 2017	Dimensionality Reduction	—Unverified	0
Fair Kernel Learning	Oct 16, 2017	BIG-bench Machine LearningDimensionality 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