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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 2241–2250 of 3304 papers

Title	Date	Tasks	Status	Hype
Bayesian inverse regression for dimension reduction with small datasets	Jun 19, 2019	Dimensionality Reductionregression	—Unverified	0
An unsupervised approach to Geographical Knowledge Discovery using street level and street network images	Jun 18, 2019	Dimensionality Reduction	—Unverified	0
Estimating a Manifold from a Tangent Bundle Learner	Jun 18, 2019	Dimensionality Reduction	—Unverified	0
Agriculture Commodity Arrival Prediction using Remote Sensing Data: Insights and Beyond	Jun 14, 2019	Dimensionality Reductionregression	—Unverified	0
Spaceland Embedding of Sparse Stochastic Graphs	Jun 13, 2019	Data VisualizationDimensionality Reduction	—Unverified	0
A Computationally Efficient Method for Defending Adversarial Deep Learning Attacks	Jun 13, 2019	Adversarial AttackDeep Learning	—Unverified	0
Classification of EEG Signals using Genetic Programming for Feature Construction	Jun 11, 2019	ClassificationDimensionality Reduction	—Unverified	0
Sparse Representation of 3D Images for Piecewise Dimensionality Reduction with High Quality Reconstruction	Jun 10, 2019	Dimensionality Reduction	—Unverified	0
Wavelet Based Dictionaries for Piecewise Dimensionality Reduction of ECG Signals	Jun 10, 2019	Dimensionality Reduction	—Unverified	0
Integrative Factorization of Bidimensionally Linked Matrices	Jun 9, 2019	Dimensionality ReductionMissing Values	CodeCode Available	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