SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 2641–2650 of 3304 papers

TitleStatusHype
Image Super-resolution via Feature-augmented Random ForestCode0
Multiple testing for outlier detection in functional data—0
Empirical Evaluation of Kernel PCA Approximation Methods in Classification Tasks—0
Effects of population- and seed bank noise on neutral evolution and efficacy of natural selection—0
Tensor Train Neighborhood Preserving Embedding—0
PFAx: Predictable Feature Analysis to Perform Control—0
From which world is your graph—0
Sparse Embedded k-Means Clustering—0
Sketching out the Details: Sketch-based Image Retrieval using Convolutional Neural Networks with Multi-stage RegressionCode0
Hierarchical Bayesian image analysis: from low-level modeling to robust supervised learning—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