SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

Showing 32213230 of 3304 papers

TitleStatusHype
Convex Formulations for Fair Principal Component AnalysisCode0
Graph Convolutional Networks Meet with High Dimensionality ReductionCode0
UCSL : A Machine Learning Expectation-Maximization framework for Unsupervised Clustering driven by Supervised LearningCode0
DC4L: Distribution Shift Recovery via Data-Driven Control for Deep Learning ModelsCode0
Graph Laplacian Regularized Graph Convolutional Networks for Semi-supervised LearningCode0
Machine learning discovery of new phases in programmable quantum simulator snapshotsCode0
Topologically Regularized Data EmbeddingsCode0
Analyzing Dynamical Brain Functional Connectivity As Trajectories on Space of Covariance MatricesCode0
Hidden Convexity of Fair PCA and Fast Solver via Eigenvalue OptimizationCode0
Active Learning for Manifold Gaussian Process RegressionCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy90.9Unverified
2tSNEClassification Accuracy51.5Unverified
3IVISClassification Accuracy46.6Unverified
4UMAPClassification Accuracy41.3Unverified
#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy71.1Unverified
2QSClassification Accuracy68Unverified