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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 1551–1560 of 3304 papers

Title	Date	Tasks	Status	Hype
SKFAC:Training Neural Networks with Faster Kronecker-Factored Approximate Curvature	Jun 1, 2021	Dimensionality Reduction	CodeCode Available	1
Wireless Federated Learning with Limited Communication and Differential Privacy	Jun 1, 2021	Dimensionality ReductionFederated Learning	—Unverified	0
WiCluster: Passive Indoor 2D/3D Positioning using WiFi without Precise Labels	May 31, 2021	Dimensionality ReductionPosition	CodeCode Available	1
Smaller Is Better: An Analysis of Instance Quantity/Quality Trade-off in Rehearsal-based Continual Learning	May 28, 2021	Continual LearningDimensionality Reduction	—Unverified	0
Visualizing Representations of Adversarially Perturbed Inputs	May 28, 2021	Dimensionality Reduction	CodeCode Available	0
An Impossibility Theorem for Node Embedding	May 27, 2021	ClusteringDimensionality Reduction	—Unverified	0
Investigating Manifold Neighborhood size for Nonlinear Analysis of LIBS Amino Acid Spectra	May 25, 2021	ClusteringDimensionality Reduction	—Unverified	0
Hierarchical Subspace Learning for Dimensionality Reduction to Improve Classification Accuracy in Large Data Sets	May 25, 2021	ClassificationDimensionality Reduction	—Unverified	0
Estimating leverage scores via rank revealing methods and randomization	May 23, 2021	Dimensionality Reduction	CodeCode Available	1
Distribution Agnostic Symbolic Representations for Time Series Dimensionality Reduction and Online Anomaly Detection	May 20, 2021	Anomaly DetectionClustering	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