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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 2631–2640 of 3304 papers

Title	Date	Tasks	Status	Hype
Image Super-resolution via Feature-augmented Random Forest	Dec 14, 2017	Content-Based Image RetrievalDictionary Learning	CodeCode Available	0
Multiple testing for outlier detection in functional data	Dec 13, 2017	Dimensionality ReductionOutlier Detection	—Unverified	0
Empirical Evaluation of Kernel PCA Approximation Methods in Classification Tasks	Dec 12, 2017	ClassificationDimensionality Reduction	—Unverified	0
Effects of population- and seed bank noise on neutral evolution and efficacy of natural selection	Dec 11, 2017	Dimensionality Reduction	—Unverified	0
Tensor Train Neighborhood Preserving Embedding	Dec 3, 2017	ClassificationDimensionality Reduction	—Unverified	0
PFAx: Predictable Feature Analysis to Perform Control	Dec 2, 2017	Dimensionality Reductionfeature selection	—Unverified	0
Sketching out the Details: Sketch-based Image Retrieval using Convolutional Neural Networks with Multi-stage Regression	Dec 1, 2017	Data AugmentationDimensionality Reduction	CodeCode Available	0
Sparse Embedded k-Means Clustering	Dec 1, 2017	ClusteringDimensionality Reduction	—Unverified	0
From which world is your graph	Dec 1, 2017	Dimensionality ReductionPosition	—Unverified	0
Simple strategies for recovering inner products from coarsely quantized random projections	Dec 1, 2017	Data CompressionDimensionality 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