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 1181–1190 of 3304 papers

TitleStatusHype
GiDR-DUN; Gradient Dimensionality Reduction -- Differences and UnificationCode1
Regression of high dimensional angular momentum states of light—0
Tree-Guided Rare Feature Selection and Logic Aggregation with Electronic Health Records Data—0
DPDR: A novel machine learning method for the Decision Process for Dimensionality Reduction—0
Scalable Differentially Private Clustering via Hierarchically Separated Trees—0
Improved Gaussian-Bernoulli Restricted Boltzmann Machines for UAV-Ground Communication Systems—0
Bayesian Learning of Parameterised Quantum Circuits—0
ARES: Locally Adaptive Reconstruction-based Anomaly ScoringCode0
"Why Here and Not There?" -- Diverse Contrasting Explanations of Dimensionality ReductionCode0
Broadband Beamforming via Linear Embedding—0
Show:102550
← PrevPage 119 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