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 1741–1750 of 3304 papers

TitleStatusHype
DAC: Deep Autoencoder-based Clustering, a General Deep Learning Framework of Representation Learning—0
Visualizing hierarchies in scRNA-seq data using a density tree-biased autoencoderCode0
Forecasting Nonnegative Time Series via Sliding Mask Method (SMM) and Latent Clustered Forecast (LCF)—0
Communication-efficient k-Means for Edge-based Machine Learning—0
RaSE: A Variable Screening Framework via Random Subspace EnsemblesCode0
Direction and Constraint in Phenotypic Evolution: Dimension Reduction and Global Proportionality in Phenotype Fluctuation and Responses—0
Robust Principal Component Analysis: A Median of Means Approach—0
Matrix Decomposition on Graphs: A Functional View—0
Optimizing Unlicensed Band Spectrum Sharing With Subspace-Based Pareto Tracing—0
System-reliability based multi-ensemble of GAN and one-class joint Gaussian distributions for unsupervised real-time structural health monitoring—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