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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 3131–3140 of 3304 papers

Title	Date	Tasks	Status	Hype
Linear Dimensionality Reduction: Survey, Insights, and Generalizations	Jun 3, 2014	Dimensionality ReductionMetric Learning	CodeCode Available	0
The constitution of visual perceptual units in the functional architecture of V1	Jun 2, 2014	ClusteringDimensionality Reduction	—Unverified	0
Automated Disease Normalization with Low Rank Approximations	Jun 1, 2014	Dimensionality ReductionLearning-To-Rank	—Unverified	0
Interpretable Semantic Vectors from a Joint Model of Brain- and Text- Based Meaning	Jun 1, 2014	Dimensionality ReductionSemantic Textual Similarity	—Unverified	0
Don't count, predict! A systematic comparison of context-counting vs. context-predicting semantic vectors	Jun 1, 2014	Dimensionality Reduction	—Unverified	0
Grassmann Averages for Scalable Robust PCA	Jun 1, 2014	Dimensionality ReductionShadow Removal	—Unverified	0
Hierarchical Feature Hashing for Fast Dimensionality Reduction	Jun 1, 2014	ClassificationDimensionality Reduction	—Unverified	0
Compact Representation for Image Classification: To Choose or to Compress?	Jun 1, 2014	ClassificationCPU	—Unverified	0
Transfer Joint Matching for Unsupervised Domain Adaptation	Jun 1, 2014	Dimensionality ReductionDomain Adaptation	—Unverified	0
Merging SVMs with Linear Discriminant Analysis: A Combined Model	Jun 1, 2014	Dimensionality ReductionObject Recognition	—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