SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 441–450 of 3304 papers

TitleStatusHype
Automatic Double Reinforcement Learning in Semiparametric Markov Decision Processes with Applications to Long-Term Causal Inference—0
Quantum Annealing for Robust Principal Component AnalysisCode0
Discovery of sustainable energy materials via the machine-learned material space—0
MRI Patterns of the Hippocampus and Amygdala for Predicting Stages of Alzheimer's Progression: A Minimal Feature Machine Learning Framework—0
Entangled Mean Estimation in High-Dimensions—0
Integrating anatomy and electrophysiology in the healthy human heart: Insights from biventricular statistical shape analysis using universal coordinatesCode0
A Stable Measure for Conditional Periodicity of Time Series using Persistent Homology—0
Multivariate Human Activity Segmentation: Systematic Benchmark with ClaSPCode0
A Graphical Approach to State Variable Selection in Off-policy Learning—0
Unified dimensionality reduction techniques in chronic liver disease detection—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