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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 2831–2840 of 3304 papers

Title	Date	Tasks	Status	Hype
Effective Dimensionality Reduction for Word Embeddings	Aug 1, 2019	Dimensionality ReductionWord Embeddings	CodeCode Available	0
In search of the weirdest galaxies in the Universe	Jul 16, 2020	ClusteringDimensionality Reduction	CodeCode Available	0
Principal Components for Neural Network Initialization	Jan 31, 2025	DenoisingDimensionality Reduction	CodeCode Available	0
Efficient Algorithms for Regularized Nonnegative Scale-invariant Low-rank Approximation Models	Mar 27, 2024	Dimensionality Reduction	CodeCode Available	0
Efficient Algorithms for t-distributed Stochastic Neighborhood Embedding	Dec 25, 2017	Dimensionality Reduction	CodeCode Available	0
Scikit-learn: Machine Learning in Python	Jan 2, 2012	BIG-bench Machine LearningClustering	CodeCode Available	0
Instance Ranking and Numerosity Reduction Using Matrix Decomposition and Subspace Learning	Apr 24, 2019	ClusteringDimensionality Reduction	CodeCode Available	0
Stacked Autoencoder Based Multi-Omics Data Integration for Cancer Survival Prediction	Jul 8, 2022	Data IntegrationDimensionality Reduction	CodeCode Available	0
Principal Manifolds and Nonlinear Dimension Reduction via Local Tangent Space Alignment	Dec 7, 2002	Data VisualizationDimensionality Reduction	CodeCode Available	0
Integrating anatomy and electrophysiology in the healthy human heart: Insights from biventricular statistical shape analysis using universal coordinates	Jan 8, 2025	AnatomyDimensionality Reduction	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