SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 1131–1140 of 3304 papers

TitleStatusHype
IAN: Iterated Adaptive Neighborhoods for manifold learning and dimensionality estimationCode1
Machine learning algorithms for three-dimensional mean-curvature computation in the level-set methodCode0
Collaborative causal inference on distributed data—0
HEFT: Homomorphically Encrypted Fusion of Biometric TemplatesCode1
On a Mechanism Framework of Autoencoders—0
Training-Time Attacks against k-Nearest Neighbors—0
May the force be with you—0
An Accelerated Doubly Stochastic Gradient Method with Faster Explicit Model Identification—0
Quantum artificial vision for defect detection in manufacturing—0
Deep Learning for Size and Microscope Feature Extraction and Classification in Oral Cancer: Enhanced Convolution Neural Network—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