SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 1611–1620 of 3304 papers

TitleStatusHype
Computational Graph Completion—0
FFTLasso: Large-Scale LASSO in the Fourier Domain—0
A novel extension of Generalized Low-Rank Approximation of Matrices based on multiple-pairs of transformations—0
Improving Problem Identification via Automated Log Clustering using Dimensionality Reduction—0
Improving Sparse Representation-Based Classification Using Local Principal Component Analysis—0
Agnostically Learning Multi-index Models with Queries—0
Improving the generalization of network based relative pose regression: dimension reduction as a regularizer—0
A Convex Sparse PCA for Feature Analysis—0
Improving the Projection of Global Structures in Data through Spanning Trees—0
A canonical correlation-based framework for performance analysis of radio access networks—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