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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 2991–3000 of 3304 papers

Title	Date	Tasks	Status	Hype
Compressive spectral embedding: sidestepping the SVD	Sep 28, 2015	ClusteringDimensionality Reduction	CodeCode Available	0
Word, graph and manifold embedding from Markov processes	Sep 18, 2015	Dimensionality ReductionWord Embeddings	—Unverified	0
Ranking Entities in the Age of Two Webs, an Application to Semantic Snippets	Sep 15, 2015	Dimensionality Reduction	—Unverified	0
Towards Making High Dimensional Distance Metric Learning Practical	Sep 15, 2015	Dimensionality ReductionMetric Learning	—Unverified	0
Geometry and dimensionality reduction of feature spaces in primary visual cortex	Sep 14, 2015	Dimensionality Reduction	—Unverified	0
Markov Boundary Discovery with Ridge Regularized Linear Models	Sep 14, 2015	Causal InferenceDimensionality Reduction	—Unverified	0
Minimum Spectral Connectivity Projection Pursuit	Sep 4, 2015	ClusteringDimensionality Reduction	CodeCode Available	0
Improving evaluation and optimization of MT systems against MEANT	Sep 1, 2015	Dimensionality ReductionMachine Translation	—Unverified	0
Topic Identification and Discovery on Text and Speech	Sep 1, 2015	Dimensionality ReductionSpeech Recognition	—Unverified	0
Factorization of Latent Variables in Distributional Semantic Models	Sep 1, 2015	Dimensionality 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