SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 1341–1350 of 3304 papers

TitleStatusHype
Hierarchical mixtures of Gaussians for combined dimensionality reduction and clustering—0
Evolutionary Echo State Network: evolving reservoirs in the Fourier space—0
Exploring Predictive States via Cantor Embeddings and Wasserstein Distance—0
CCP: Correlated Clustering and Projection for Dimensionality ReductionCode0
Theoretical Error Performance Analysis for Variational Quantum Circuit Based Functional RegressionCode0
Adaptive Weighted Nonnegative Matrix Factorization for Robust Feature RepresentationCode0
Click prediction boosting via Bayesian hyperparameter optimization based ensemble learning pipelines—0
Unifying Summary Statistic Selection for Approximate Bayesian ComputationCode0
First-Order Algorithms for Min-Max Optimization in Geodesic Metric Spaces—0
Classification at the Accuracy Limit -- Facing the Problem of Data Ambiguity—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