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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 3231–3240 of 3304 papers

Title	Date	Tasks	Status	Hype
Group Component Analysis for Multiblock Data: Common and Individual Feature Extraction	Dec 17, 2012	blind source separationClustering	—Unverified	0
Learning Mixtures of Arbitrary Distributions over Large Discrete Domains	Dec 7, 2012	2kDimensionality Reduction	—Unverified	0
Latent Coincidence Analysis: A Hidden Variable Model for Distance Metric Learning	Dec 1, 2012	Dimensionality ReductionMetric Learning	—Unverified	0
A Geometric take on Metric Learning	Dec 1, 2012	Dimensionality ReductionMetric Learning	—Unverified	0
Collaborative Gaussian Processes for Preference Learning	Dec 1, 2012	Active LearningDimensionality Reduction	—Unverified	0
Gradient-based kernel method for feature extraction and variable selection	Dec 1, 2012	Dimensionality ReductionVariable Selection	—Unverified	0
Feature-aware Label Space Dimension Reduction for Multi-label Classification	Dec 1, 2012	ClassificationCompressive Sensing	—Unverified	0
Super-Bit Locality-Sensitive Hashing	Dec 1, 2012	Dimensionality ReductionRetrieval	—Unverified	0
Random Projections for Linear Support Vector Machines	Nov 26, 2012	Dimensionality ReductionGeneral Classification	—Unverified	0
Accelerated Canonical Polyadic Decomposition by Using Mode Reduction	Nov 15, 2012	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