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 2881–2890 of 3304 papers

TitleStatusHype
Probabilistic Data Analysis with Probabilistic ProgrammingCode0
Training Echo State Networks with Regularization through Dimensionality Reduction—0
Ultra High-Dimensional Nonlinear Feature Selection for Big Biological Data—0
Bayesian Learning of Dynamic Multilayer Networks—0
Robust High-Dimensional Linear Regression—0
Exponential Family Embeddings—0
Domain Adaptation for Authorship Attribution: Improved Structural Correspondence Learning—0
TransG : A Generative Model for Knowledge Graph Embedding—0
Random Positive-Only Projections: PPMI-Enabled Incremental Semantic Space Construction—0
Robust Co-occurrence Quantification for Lexical Distributional Semantics—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