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 1611–1620 of 3304 papers

TitleStatusHype
Improving Lexical Semantics for Sentential Semantics: Modeling Selectional Preference and Similar Words in a Latent Variable Model—0
Building an Efficient Intrusion Detection System Based on Feature Selection and Ensemble Classifier—0
Improving Oral Cancer Outcomes Through Machine Learning and Dimensionality Reduction—0
Improving Problem Identification via Automated Log Clustering using Dimensionality Reduction—0
Efficient and Scalable Batch Bayesian Optimization Using K-Means—0
Deep Manifold Computing and Visualization Using Elastic Locally Isometric Smoothness—0
Improving the generalization of network based relative pose regression: dimension reduction as a regularizer—0
Efficient and Robust Bayesian Selection of Hyperparameters in Dimension Reduction for Visualization—0
Improving the Projection of Global Structures in Data through Spanning Trees—0
Bounds on Causal Effects and Application to High Dimensional Data—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