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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 2181–2190 of 3304 papers

Title	Date	Tasks	Status	Hype
A Flexible Framework for Anomaly Detection via Dimensionality Reduction	Sep 9, 2019	Active LearningAnomaly Detection	CodeCode Available	0
Quantized Fisher Discriminant Analysis	Sep 6, 2019	BIG-bench Machine LearningDimensionality Reduction	CodeCode Available	0
Solving Interpretable Kernel Dimension Reduction	Sep 6, 2019	ClusteringDimensionality Reduction	CodeCode Available	0
Restricted Minimum Error Entropy Criterion for Robust Classification	Sep 6, 2019	ClassificationDimensionality Reduction	—Unverified	0
Spectral Non-Convex Optimization for Dimension Reduction with Hilbert-Schmidt Independence Criterion	Sep 6, 2019	ClusteringDimensionality Reduction	—Unverified	0
Fusing Vector Space Models for Domain-Specific Applications	Sep 5, 2019	Dimensionality ReductionWord Embeddings	—Unverified	0
Latent Gaussian process with composite likelihoods and numerical quadrature	Sep 4, 2019	ClusteringDimensionality Reduction	—Unverified	0
Progressive Disentanglement Using Relevant Factor VAE	Sep 4, 2019	Dimensionality ReductionDisentanglement	—Unverified	0
Lifetime Ruin under High-watermark Fees and Drift Uncertainty	Sep 3, 2019	Dimensionality ReductionVocal Bursts Intensity Prediction	—Unverified	0
Mixture Probabilistic Principal Geodesic Analysis	Sep 3, 2019	ClusteringDimensionality Reduction	—Unverified	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