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 2071–2080 of 3304 papers

TitleStatusHype
Incentives and co-evolution: Steering linear dynamical systems with noncooperative agents—0
Inceptive Event Time-Surfaces for Object Classification Using Neuromorphic Cameras—0
Incomplete Pivoted QR-based Dimensionality Reduction—0
Incremental Ensemble Gaussian Processes—0
Individualized Multilayer Tensor Learning with An Application in Imaging Analysis—0
Inductive Regularized Learning of Kernel Functions—0
Inference and Interference: The Role of Clipping, Pruning and Loss Landscapes in Differentially Private Stochastic Gradient Descent—0
Inference for Regression with Variables Generated by AI or Machine Learning—0
Influ\^encia de T\'ecnicas N\~ao-supervisionadas de Redu \~ao de Dimensionalidade para Organiza \~ao Flex\' de Documentos (The Unsupervised Dimensionality Reduction Weight on Flexible Document Organization)[In Portuguese]—0
InfoClus: Informative Clustering of High-dimensional Data Embeddings—0
Show:102550
← PrevPage 208 of 331Next →
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