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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 2851–2860 of 3304 papers

Title	Date	Tasks	Status	Hype
Uniform-in-Phase-Space Data Selection with Iterative Normalizing Flows	Dec 28, 2021	Data CompressionDimensionality Reduction	CodeCode Available	0
Efficiently Visualizing Large Graphs	Oct 17, 2023	Dimensionality ReductionGraph Embedding	CodeCode Available	0
Multivariate Probabilistic CRPS Learning with an Application to Day-Ahead Electricity Prices	Mar 17, 2023	Dimensionality Reduction	CodeCode Available	0
Efficient Manifold and Subspace Approximations with Spherelets	Jun 26, 2017	ClusteringData Compression	CodeCode Available	0
Efficient Multidimensional Functional Data Analysis Using Marginal Product Basis Systems	Jul 30, 2021	Dimensionality ReductionTensor Decomposition	CodeCode Available	0
Deep Linear Discriminant Analysis	Nov 15, 2015	Dimensionality Reduction	CodeCode Available	0
The neighborhood lattice for encoding partial correlations in a Hilbert space	Nov 3, 2017	Dimensionality Reductionregression	CodeCode Available	0
Interactive Latent Interpolation on MNIST Dataset	Oct 15, 2020	Dimensionality Reduction	CodeCode Available	0
Efficient Online Learning of Optimal Rankings: Dimensionality Reduction via Gradient Descent	Nov 5, 2020	Dimensionality Reduction	CodeCode Available	0
Interpetable Target-Feature Aggregation for Multi-Task Learning based on Bias-Variance Analysis	Jun 12, 2024	ClusteringDimensionality 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