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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 2231–2240 of 3304 papers

Title	Date	Tasks	Status	Hype
A data-driven approach for multiscale elliptic PDEs with random coefficients based on intrinsic dimension reduction	Jul 1, 2019	Dimensionality Reduction	—Unverified	0
Nature Inspired Dimensional Reduction Technique for Fast and Invariant Visual Feature Extraction	Jul 1, 2019	Dimensionality Reduction	—Unverified	0
Understanding Memory Modules on Learning Simple Algorithms	Jul 1, 2019	Dimensionality Reduction	—Unverified	0
An Improvement of PAA on Trend-Based Approximation for Time Series	Jun 28, 2019	Anomaly DetectionDimensionality Reduction	—Unverified	0
Anomaly Subsequence Detection with Dynamic Local Density for Time Series	Jun 28, 2019	Anomaly DetectionDensity Estimation	—Unverified	0
Tuning-Free Disentanglement via Projection	Jun 27, 2019	Dimensionality ReductionDisentanglement	—Unverified	0
Learning Fair Representations for Kernel Models	Jun 27, 2019	Dimensionality ReductionFairness	CodeCode Available	0
Transfer Learning for Segmenting Dimensionally-Reduced Hyperspectral Images	Jun 23, 2019	Dimensionality ReductionEarth Observation	—Unverified	0
Fisher and Kernel Fisher Discriminant Analysis: Tutorial	Jun 22, 2019	Dimensionality Reduction	CodeCode Available	0
Screening Sinkhorn Algorithm for Regularized Optimal Transport	Jun 20, 2019	Dimensionality ReductionDomain Adaptation	CodeCode Available	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