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 2281–2290 of 3304 papers

TitleStatusHype
Trace Quotient with Sparsity Priors for Learning Low Dimensional Image Representations—0
Trace transform based method for color image domain identification—0
Trainable Compound Activation Functions for Machine Learning—0
Training Artificial Neural Networks by Coordinate Search Algorithm—0
Training Echo State Networks with Regularization through Dimensionality Reduction—0
Training (Overparametrized) Neural Networks in Near-Linear Time—0
Training-Time Attacks against k-Nearest Neighbors—0
Transcription Factor-DNA Binding Via Machine Learning Ensembles—0
Transfer Joint Matching for Unsupervised Domain Adaptation—0
Transfer learning-assisted inverse modeling in nanophotonics based on mixture density networks—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