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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 171–180 of 3304 papers

Title	Date	Tasks	Status	Hype
Perplexity-free Parametric t-SNE	Oct 3, 2020	Dimensionality Reduction	CodeCode Available	1
Effective Sample Size, Dimensionality, and Generalization in Covariate Shift Adaptation	Oct 2, 2020	Dimensionality ReductionDomain Adaptation	CodeCode Available	1
Deep Learning of Individual Aesthetics	Sep 24, 2020	Deep LearningDimensionality Reduction	CodeCode Available	1
Joint and Progressive Subspace Analysis (JPSA) with Spatial-Spectral Manifold Alignment for Semi-Supervised Hyperspectral Dimensionality Reduction	Sep 21, 2020	Dimensionality Reduction	CodeCode Available	1
Going Beyond T-SNE: Exposing whatlies in Text Embeddings	Sep 4, 2020	Dimensionality ReductionSentence	CodeCode Available	1
Improving the HardNet Descriptor	Jul 19, 2020	Dimensionality ReductionImage Retrieval	CodeCode Available	1
Trajectories, bifurcations and pseudotime in large clinical datasets: applications to myocardial infarction and diabetes data	Jul 7, 2020	ClusteringData Visualization	CodeCode Available	1
A New Basis for Sparse Principal Component Analysis	Jul 1, 2020	ClusteringDimensionality Reduction	CodeCode Available	1
Physics-aware registration based auto-encoder for convection dominated PDEs	Jun 28, 2020	Dimensionality Reduction	CodeCode Available	1
Invertible Concept-based Explanations for CNN Models with Non-negative Concept Activation Vectors	Jun 27, 2020	ClusteringDimensionality Reduction	CodeCode Available	1

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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