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 2021–2030 of 3304 papers

TitleStatusHype
Sensitivity Analysis for Active Sampling, with Applications to the Simulation of Analog Circuits—0
Sensitivity Analysis for Causal Mediation through Text: an Application to Political Polarization—0
Sentence Meta-Embeddings for Unsupervised Semantic Textual Similarity—0
SenticNet 4: A Semantic Resource for Sentiment Analysis Based on Conceptual Primitives—0
Sequential Dimensionality Reduction for Extracting Localized Features—0
Sequential Labeling with online Deep Learning—0
Sequential Learning of Principal Curves: Summarizing Data Streams on the Fly—0
Sequential Low-Rank Change Detection—0
Sequential Principal Curves Analysis—0
SGEN: Single-cell Sequencing Graph Self-supervised Embedding Network—0
Show:102550
← PrevPage 203 of 331Next →
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