SOTAVerified

Dimensionality Reduction

Dimensionality reduction is the task of reducing the dimensionality of a dataset.

( Image credit: openTSNE )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 2911–2920 of 3304 papers

TitleStatusHype
A Tale of Two Bases: Local-Nonlocal Regularization on Image Patches with Convolution Framelets—0
Property-driven State-Space Coarsening for Continuous Time Markov Chains—0
Sequential Principal Curves Analysis—0
Unifying Geometric Features and Facial Action Units for Improved Performance of Facial Expression Analysis—0
Trace Quotient Meets Sparsity: A Method for Learning Low Dimensional Image Representations—0
Efficient Large-Scale Similarity Search Using Matrix Factorization—0
Decoding Emotional Experience through Physiological Signal Processing—0
Mixtape Application: Music Map Methodology and Evaluation—0
Learning From Hidden Traits: Joint Factor Analysis and Latent Clustering—0
Dimensionality Reduction on SPD Manifolds: The Emergence of Geometry-Aware Methods—0
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All datasetsMCAEMNIST

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy90.9—Unverified
2tSNEClassification Accuracy51.5—Unverified
3IVISClassification Accuracy46.6—Unverified
4UMAPClassification Accuracy41.3—Unverified
#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy71.1—Unverified
2QSClassification Accuracy68—Unverified