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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 3291–3300 of 3304 papers

Title	Date	Tasks	Status	Hype
Gaussian-process factor analysis for low-dimensional single-trial analysis of neural population activity	Dec 1, 2008	Dimensionality Reduction	—Unverified	0
Localized Sliced Inverse Regression	Dec 1, 2008	Dimensionality ReductionGeneral Classification	—Unverified	0
Dimensionality Reduction for Data in Multiple Feature Representations	Dec 1, 2008	ClusteringDimensionality Reduction	—Unverified	0
Bayesian Exponential Family PCA	Dec 1, 2008	Bayesian InferenceDimensionality Reduction	—Unverified	0
Supervised Exponential Family Principal Component Analysis via Convex Optimization	Dec 1, 2008	Dimensionality Reductionglobal-optimization	—Unverified	0
Fast High-dimensional Kernel Summations Using the Monte Carlo Multipole Method	Dec 1, 2008	Dimensionality ReductionVocal Bursts Intensity Prediction	—Unverified	0
Diffeomorphic Dimensionality Reduction	Dec 1, 2008	Dimensionality Reduction	—Unverified	0
Visualizing Data using t-SNE	Nov 1, 2008	Dimensionality Reduction	—Unverified	0
3D Face Recognition with Sparse Spherical Representations	Oct 29, 2008	Dimensionality ReductionFace Recognition	—Unverified	0
People Tracking with the Laplacian Eigenmaps Latent Variable Model	Dec 1, 2007	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