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 1781–1790 of 3304 papers

TitleStatusHype
Order Embeddings from Merged Ontologies using Sketching—0
Large-Scale Extended Granger Causality for Classification of Marijuana Users From Functional MRI—0
Analyzing movies to predict their commercial viability for producers—0
A Linearly Convergent Algorithm for Distributed Principal Component AnalysisCode0
Protecting Big Data Privacy Using Randomized Tensor Network Decomposition and Dispersed Tensor Computation—0
Factor Analysis, Probabilistic Principal Component Analysis, Variational Inference, and Variational Autoencoder: Tutorial and Survey—0
A new parsimonious method for classifying Cancer Tissue-of-Origin Based on DNA Methylation 450K data—0
On the Importance of Distraction-Robust Representations for Robot Learning—0
Graph Learning via Spectral Densification—0
Graph Neural Network Acceleration via Matrix Dimension Reduction—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