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Dimensionality Reduction

Dimensionality reduction is the task of reducing the dimensionality of a dataset.

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Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 2321–2330 of 3304 papers

Title	Date	Tasks	Status	Hype
Learning the dynamics of technical trading strategies	Mar 6, 2019	Dimensionality ReductionTime Series	CodeCode Available	1
Deep Random Splines for Point Process Intensity Estimation of Neural Population Data	Mar 6, 2019	Dimensionality ReductionGaussian Processes	CodeCode Available	0
GraphVite: A High-Performance CPU-GPU Hybrid System for Node Embedding	Mar 2, 2019	CPUDimensionality Reduction	CodeCode Available	0
Efficient Contextual Representation Learning Without Softmax Layer	Feb 28, 2019	Dimensionality ReductionLanguage Modeling	—Unverified	0
Multi-Criteria Dimensionality Reduction with Applications to Fairness	Feb 28, 2019	Dimensionality ReductionFairness	CodeCode Available	0
High-dimensional Bayesian optimization using low-dimensional feature spaces	Feb 27, 2019	Bayesian OptimizationDimensionality Reduction	CodeCode Available	0
Deep active subspaces - a scalable method for high-dimensional uncertainty propagation	Feb 27, 2019	Dimensionality ReductionUncertainty Quantification	CodeCode Available	1
Ordinal Distance Metric Learning with MDS for Image Ranking	Feb 27, 2019	Dimensionality ReductionMetric Learning	—Unverified	0
A Review, Framework and R toolkit for Exploring, Evaluating, and Comparing Visualizations	Feb 22, 2019	Dimensionality Reduction	—Unverified	0
Deep Learning Multidimensional Projections	Feb 21, 2019	BIG-bench Machine LearningDeep Learning	—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