SOTAVerified

Dimensionality Reduction

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

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Papers

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Showing 1631–1640 of 3304 papers

TitleStatusHype
FedNE: Surrogate-Assisted Federated Neighbor Embedding for Dimensionality Reduction—0
Inference and Interference: The Role of Clipping, Pruning and Loss Landscapes in Differentially Private Stochastic Gradient Descent—0
Federated Sufficient Dimension Reduction Through High-Dimensional Sparse Sliced Inverse Regression—0
Compressive Sensing Approaches for Sparse Distribution Estimation Under Local Privacy—0
Influ\^encia de T\'ecnicas N\~ao-supervisionadas de Redu \~ao de Dimensionalidade para Organiza \~ao Flex\' de Documentos (The Unsupervised Dimensionality Reduction Weight on Flexible Document Organization)[In Portuguese]—0
InfoClus: Informative Clustering of High-dimensional Data Embeddings—0
Information loss from dimensionality reduction in 5D-Gaussian spectral data—0
Information Processing by Neuron Populations in the Central Nervous System: Mathematical Structure of Data and Operations—0
Information retrieval in single cell chromatin analysis using TF-IDF transformation methods—0
Federated Multilinear Principal Component Analysis with Applications in Prognostics—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