SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 2131–2140 of 3304 papers

TitleStatusHype
Statistical guarantees for generative models without domination—0
Statistical physics, Bayesian inference and neural information processing—0
Statistical tuning of artificial neural network—0
STDP enables spiking neurons to detect hidden causes of their inputs—0
Steering Distortions to Preserve Classes and Neighbors in Supervised Dimensionality Reduction—0
Stochastic Approximation Algorithms for Principal Component Analysis—0
Stochastic Approximation for Online Tensorial Independent Component Analysis—0
Stochastic Bottleneck: Rateless Auto-Encoder for Flexible Dimensionality Reduction—0
Performance-Complexity Tradeoffs in Greedy Weak Submodular Maximization with Random Sampling—0
Stochastic Linear Bandits with Hidden Low Rank Structure—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