SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 611–620 of 3304 papers

TitleStatusHype
Full-dimensional characterisation of time-warped spike-time stimulus-response distribution geometries—0
Transfer learning-assisted inverse modeling in nanophotonics based on mixture density networks—0
Automatic dimensionality reduction of Twin-in-the-Loop Observers—0
Comprehensive OOD Detection Improvements—0
Content-Aware Tweet Location Inference using Quadtree Spatial Partitioning and Jaccard-Cosine Word Embedding—0
Differentially Private Sliced Inverse Regression: Minimax Optimality and Algorithm—0
Mobile Contactless Palmprint Recognition: Use of Multiscale, Multimodel Embeddings—0
Sparse PCA with False Discovery Rate Controlled Variable Selection—0
Image Similarity using An Ensemble of Context-Sensitive ModelsCode0
Semantic-Preserving Feature Partitioning for Multi-View Ensemble Learning—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