SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 2011–2020 of 3304 papers

TitleStatusHype
SemEval-2012 Task 7: Choice of Plausible Alternatives: An Evaluation of Commonsense Causal Reasoning—0
Semi-orthogonal Non-negative Matrix Factorization with an Application in Text Mining—0
Semi-supervised deep learning for high-dimensional uncertainty quantification—0
Semi-Supervised Deep Learning Using Improved Unsupervised Discriminant Projection—0
Semi-supervised Deep Representation Learning for Multi-View Problems—0
Semi-supervised Fisher vector network—0
Semi-supervised Learning based on Distributionally Robust Optimization—0
Semi-supervised Learning with Explicit Relationship Regularization—0
Semi-Supervised Quantile Estimation: Robust and Efficient Inference in High Dimensional Settings—0
Semi-supervised Regression using Hessian energy with an application to semi-supervised 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