SOTAVerified

Dimensionality Reduction

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

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Papers

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Showing 2871–2880 of 3304 papers

TitleStatusHype
ADAGIO: Fast Data-aware Near-Isometric Linear EmbeddingsCode0
Recursive nearest agglomeration (ReNA): fast clustering for approximation of structured signalsCode0
Supervised multiway factorizationCode0
Peacock Bundles: Bundle Coloring for Graphs with Globality-Locality Trade-off—0
Constraint matrix factorization for space variant PSFs field restorationCode0
Robust Discriminative Clustering with Sparse Regularizers—0
Large Scale Behavioral Analytics via Topical Interaction—0
Interacting with Massive Behavioral Data—0
Comparison among dimensionality reduction techniques based on Random Projection for cancer classification—0
Unsupervised Feature Selection Based on the Morisita Estimator of Intrinsic Dimension—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