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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 2791–2800 of 3304 papers

Title	Date	Tasks	Status	Hype
Deep Temporal Clustering: Fully unsupervised learning of time-domain features	Jan 1, 2018	ClusteringDimensionality Reduction	CodeCode Available	0
The Fast Johnson-Lindenstrauss Transform is Even Faster	Apr 4, 2022	Dimensionality Reduction	CodeCode Available	0
Clustering Noisy Signals with Structured Sparsity Using Time-Frequency Representation	Oct 18, 2015	ClusteringDimensionality Reduction	CodeCode Available	0
DNN Feature Map Compression using Learned Representation over GF(2)	Aug 15, 2018	Dimensionality ReductionGeneral Classification	CodeCode Available	0
Scalable Geometric Learning with Correlation-Based Functional Brain Networks	Mar 31, 2025	Dimensionality Reduction	CodeCode Available	0
Predicting Fatigue Crack Growth via Path Slicing and Re-Weighting	Sep 13, 2023	Decision MakingDimensionality Reduction	CodeCode Available	0
SqueezeFit: Label-aware dimensionality reduction by semidefinite programming	Dec 6, 2018	ClassificationDimensionality Reduction	CodeCode Available	0
Multidimensional Scaling, Sammon Mapping, and Isomap: Tutorial and Survey	Sep 17, 2020	Dimensionality ReductionSurvey	CodeCode Available	0
Visualization of Emergency Department Clinical Data for Interpretable Patient Phenotyping	Jul 5, 2019	Decision MakingDimensionality Reduction	CodeCode Available	0
Bayesian latent structure discovery from multi-neuron recordings	Oct 26, 2016	Bayesian InferenceClustering	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