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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 3161–3170 of 3304 papers

Title	Date	Tasks	Status	Hype
Dimensionality reduction with subgaussian matrices: a unified theory	Feb 17, 2014	Dimensionality Reduction	—Unverified	0
Distributed Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models	Feb 6, 2014	Dimensionality ReductionGaussian Processes	CodeCode Available	0
Applying Supervised Learning Algorithms and a New Feature Selection Method to Predict Coronary Artery Disease	Feb 3, 2014	Dimensionality Reductionfeature selection	—Unverified	0
Human Activity Recognition using Smartphone	Jan 30, 2014	Active LearningActivity Recognition	—Unverified	0
Highly comparative feature-based time-series classification	Jan 15, 2014	ClassificationDimensionality Reduction	—Unverified	0
A Bilinear Programming Approach for Multiagent Planning	Jan 15, 2014	Dimensionality Reduction	—Unverified	0
Factorized Point Process Intensities: A Spatial Analysis of Professional Basketball	Jan 5, 2014	Dimensionality Reduction	CodeCode Available	0
A Large Scale Evaluation of Distributional Semantic Models: Parameters, Interactions and Model Selection	Jan 1, 2014	Dimensionality ReductionInformation Retrieval	—Unverified	0
Learning Deep Representations By Distributed Random Samplings	Dec 16, 2013	ClusteringDimensionality Reduction	—Unverified	0
Sparse Matrix-based Random Projection for Classification	Dec 12, 2013	ClassificationDimensionality 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