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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 2721–2730 of 3304 papers

Title	Date	Tasks	Status	Hype
Reducing the dimensionality of data using tempered distributions	Mar 12, 2019	Dimensionality Reduction	CodeCode Available	0
Mixtures of Skewed Matrix Variate Bilinear Factor Analyzers	Sep 7, 2018	ClusteringDimensionality Reduction	CodeCode Available	0
Dimension Reduction for Data with Heterogeneous Missingness	Sep 24, 2021	Dimensionality ReductionMissing Values	CodeCode Available	0
VAMPnets: Deep learning of molecular kinetics	Oct 16, 2017	ClusteringDeep Learning	CodeCode Available	0
Spectral Overlap and a Comparison of Parameter-Free, Dimensionality Reduction Quality Metrics	Jul 3, 2019	Dimensionality ReductionHyperparameter Optimization	CodeCode Available	0
Dimensionality Reduction and (Bucket) Ranking: a Mass Transportation Approach	Oct 15, 2018	Dimensionality Reduction	CodeCode Available	0
Compressive spectral embedding: sidestepping the SVD	Sep 28, 2015	ClusteringDimensionality Reduction	CodeCode Available	0
ICA-based Resting-State Networks Obtained on Large Autism fMRI Dataset ABIDE	Dec 18, 2024	Dimensionality Reduction	CodeCode Available	0
Roweis Discriminant Analysis: A Generalized Subspace Learning Method	Oct 11, 2019	Dimensionality ReductionFace Recognition	CodeCode Available	0
A more globally accurate dimensionality reduction method using triplets	Mar 1, 2018	Dimensionality ReductionTriplet	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