SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 901–910 of 3304 papers

TitleStatusHype
Ellipsoid fitting with the Cayley transformCode0
Linear Convergence of Reshuffling Kaczmarz Methods With Sparse Constraints—0
Dynamic Security Region of Natural Gas Systems in Integrated Electricity-Gas Systems—0
Hyperspectral Image Analysis with Subspace Learning-based One-Class Classification—0
Wireless Channel Charting: Theory, Practice, and Applications—0
A Neural Network Transformer Model for Composite Microstructure Homogenization—0
Dimensionality Reduction as Probabilistic Inference—0
Uncovering the Inner Workings of STEGO for Safe Unsupervised Semantic SegmentationCode1
Online Recognition of Incomplete Gesture Data to Interface Collaborative RobotsCode0
Fast emulation of cosmological density fields based on dimensionality reduction and supervised machine-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