SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 1511–1520 of 3304 papers

TitleStatusHype
Feature Grouping and Sparse Principal Component Analysis with Truncated RegularizationCode0
Regularisation for PCA- and SVD-type matrix factorisations—0
Efficient Tensor Contraction via Fast Count Sketch—0
Partial Maximum Correntropy Regression for Robust Trajectory Decoding from Noisy Epidural Electrocorticographic Signals—0
Multi-Class Classification of Blood Cells -- End to End Computer Vision based diagnosis case study—0
Bounds on Causal Effects and Application to High Dimensional Data—0
Objective discovery of dominant dynamical processes with intelligible machine learningCode0
3D Shape Registration Using Spectral Graph Embedding and Probabilistic Matching—0
Low-rank Characteristic Tensor Density Estimation Part II: Compression and Latent Density EstimationCode0
SKFAC: Training Neural Networks With Faster Kronecker-Factored Approximate CurvatureCode1
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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