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 1351–1360 of 3304 papers

TitleStatusHype
Machine learning discovery of new phases in programmable quantum simulator snapshotsCode0
Artificial Intelligence and Dimensionality Reduction: Tools for approaching future communications—0
Supervised Multivariate Learning with Simultaneous Feature Auto-grouping and Dimension Reduction—0
Funnels: Exact maximum likelihood with dimensionality reductionCode0
Triangle Attack: A Query-efficient Decision-based Adversarial AttackCode1
Robust factored principal component analysis for matrix-valued outlier accommodation and detection—0
Risk and optimal policies in bandit experiments—0
Reducing Catastrophic Forgetting in Self Organizing Maps with Internally-Induced Generative Replay—0
A Cross Entropy test allows quantitative statistical comparison of t-SNE and UMAP representations—0
Learnable Faster Kernel-PCA for Nonlinear Fault Detection: Deep Autoencoder-Based Realization—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