SOTAVerified

Dimensionality Reduction

Dimensionality reduction is the task of reducing the dimensionality of a dataset.

( Image credit: openTSNE )

Papers

Showing 30413050 of 3304 papers

TitleStatusHype
oASIS: Adaptive Column Sampling for Kernel Matrix Approximation0
Bayesian Sparse Tucker Models for Dimension Reduction and Tensor CompletionCode0
Spike and Slab Gaussian Process Latent Variable Models0
Trees Assembling Mann Whitney Approach for Detecting Genome-wide Joint Association among Low Marginal Effect loci0
Self-Expressive Decompositions for Matrix Approximation and Clustering0
Using PCA to Efficiently Represent State Spaces0
High-Order Low-Rank Tensors for Semantic Role Labeling0
NASARI: a Novel Approach to a Semantically-Aware Representation of Items0
Robust Principal Component Analysis on Graphs0
Effective Discriminative Feature Selection with Non-trivial Solutions0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy90.9Unverified
2tSNEClassification Accuracy51.5Unverified
3IVISClassification Accuracy46.6Unverified
4UMAPClassification Accuracy41.3Unverified
#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy71.1Unverified
2QSClassification Accuracy68Unverified