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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 2271–2280 of 3304 papers

Title	Date	Tasks	Status	Hype
A Data-Driven and Distributed Approach to Sparse Signal Representation and Recovery	May 1, 2019	Dimensionality Reduction	—Unverified	0
Locally Linear Unsupervised Feature Selection	May 1, 2019	Dimensionality Reductionfeature selection	—Unverified	0
Dimensionality Reduction for Representing the Knowledge of Probabilistic Models	May 1, 2019	ClassificationDimensionality Reduction	—Unverified	0
Representation-Constrained Autoencoders and an Application to Wireless Positioning	May 1, 2019	Dimensionality Reduction	—Unverified	0
Online Learning for Supervised Dimension Reduction	May 1, 2019	Dimensionality Reductionregression	—Unverified	0
Learning Entropic Wasserstein Embeddings	May 1, 2019	Dimensionality Reduction	—Unverified	0
Detecting Adversarial Examples through Nonlinear Dimensionality Reduction	Apr 30, 2019	Density EstimationDimensionality Reduction	CodeCode Available	0
Statistical feature embedding for heart sound classification	Apr 26, 2019	ClassificationDimensionality Reduction	—Unverified	0
Recommending research articles to consumers of online vaccination information	Apr 26, 2019	ArticlesDimensionality Reduction	CodeCode Available	0
Instance Ranking and Numerosity Reduction Using Matrix Decomposition and Subspace Learning	Apr 24, 2019	ClusteringDimensionality Reduction	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