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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 2511–2520 of 3304 papers

Title	Date	Tasks	Status	Hype
Multi-view Reconstructive Preserving Embedding for Dimension Reduction	Jul 25, 2018	Dimensionality ReductionDocument Classification	—Unverified	0
Space-Time Extension of the MEM Approach for Electromagnetic Neuroimaging	Jul 24, 2018	Dimensionality Reduction	—Unverified	0
A Generative-Discriminative Basis Learning Framework to Predict Clinical Severity from Resting State Functional MRI Data	Jul 24, 2018	Dimensionality Reductionregression	—Unverified	0
Recurrent Neural Networks for Long and Short-Term Sequential Recommendation	Jul 23, 2018	Dimensionality ReductionRecommendation Systems	—Unverified	0
Tree-structured multi-stage principal component analysis (TMPCA): theory and applications	Jul 22, 2018	Dimensionality ReductionGeneral Classification	—Unverified	0
A Trace Lasso Regularized L1-norm Graph Cut for Highly Correlated Noisy Hyperspectral Image	Jul 22, 2018	Dimensionality Reduction	—Unverified	0
Isolation Kernel and Its Effect on SVM	Jul 19, 2018	Dimensionality ReductionGeneral Classification	—Unverified	0
Unsupervised Metric Learning in Presence of Missing Data	Jul 19, 2018	Dimensionality ReductionMatrix Completion	CodeCode Available	0
Parametric generation of conditional geological realizations using generative neural networks	Jul 13, 2018	Dimensionality Reduction	CodeCode Available	0
Channel Charting: Locating Users within the Radio Environment using Channel State Information	Jul 13, 2018	Dimensionality ReductionScheduling	—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