SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 2481–2490 of 3304 papers

TitleStatusHype
A Bilinear Programming Approach for Multiagent Planning—0
A Bootstrap Method for Error Estimation in Randomized Matrix Multiplication—0
A Brief Survey on Representation Learning based Graph Dimensionality Reduction Techniques—0
Abstraction and Symbolic Execution of Deep Neural Networks with Bayesian Approximation of Hidden Features—0
A canonical correlation-based framework for performance analysis of radio access networks—0
A case study : Influence of Dimension Reduction on regression trees-based Algorithms -Predicting Aeronautics Loads of a Derivative Aircraft—0
A Category Space Approach to Supervised Dimensionality Reduction—0
Accelerated Canonical Polyadic Decomposition by Using Mode Reduction—0
Accelerated partial separable model using dimension-reduced optimization technique for ultra-fast cardiac MRI—0
Accelerated Search for Non-Negative Greedy Sparse Decomposition via Dimensionality Reduction—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