SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 3131–3140 of 3304 papers

TitleStatusHype
Linear Dimensionality Reduction: Survey, Insights, and GeneralizationsCode0
The constitution of visual perceptual units in the functional architecture of V1—0
Automated Disease Normalization with Low Rank Approximations—0
Merging SVMs with Linear Discriminant Analysis: A Combined Model—0
Transfer Joint Matching for Unsupervised Domain Adaptation—0
A Compact and Discriminative Face Track Descriptor—0
Grassmann Averages for Scalable Robust PCA—0
Hierarchical Feature Hashing for Fast Dimensionality Reduction—0
Compact Representation for Image Classification: To Choose or to Compress?—0
Interpretable Semantic Vectors from a Joint Model of Brain- and Text- Based Meaning—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