SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

Showing 21612170 of 3304 papers

TitleStatusHype
Spectral Non-Convex Optimization for Dimension Reduction with Hilbert-Schmidt Independence Criterion0
Solving Interpretable Kernel Dimension ReductionCode0
Quantized Fisher Discriminant AnalysisCode0
Restricted Minimum Error Entropy Criterion for Robust Classification0
Fusing Vector Space Models for Domain-Specific Applications0
Progressive Disentanglement Using Relevant Factor VAE0
Latent Gaussian process with composite likelihoods and numerical quadrature0
Lifetime Ruin under High-watermark Fees and Drift Uncertainty0
Mixture Probabilistic Principal Geodesic Analysis0
A study of semantic augmentation of word embeddings for extractive summarization0
Show:102550
← PrevPage 217 of 331Next →

Benchmark Results

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