SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

Showing 29512960 of 3304 papers

TitleStatusHype
Kernel Principal Component Analysis and its Applications in Face Recognition and Active Shape ModelsCode0
Neural Networks Perform Sufficient Dimension ReductionCode0
The Price of Fair PCA: One Extra DimensionCode0
DeepHYDRA: Resource-Efficient Time-Series Anomaly Detection in Dynamically-Configured SystemsCode0
Stochastic Neighbor Embedding with Gaussian and Student-t Distributions: Tutorial and SurveyCode0
Exact and Approximation Algorithms for Sparse PCACode0
NeuroDAVIS: A neural network model for data visualizationCode0
NeuroMapper: In-browser Visualizer for Neural Network TrainingCode0
A Large-Scale Sensitivity Analysis on Latent Embeddings and Dimensionality Reductions for Text SpatializationsCode0
Knowledge Base Index Compression via Dimensionality and Precision ReductionCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy90.9Unverified
2tSNEClassification Accuracy51.5Unverified
3IVISClassification Accuracy46.6Unverified
4UMAPClassification Accuracy41.3Unverified
#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy71.1Unverified
2QSClassification Accuracy68Unverified