SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 1021–1030 of 3304 papers

TitleStatusHype
Time-Efficient Reward Learning via Visually Assisted Cluster Ranking—0
Universal Feature Selection Tool (UniFeat): An Open-Source Tool for Dimensionality ReductionCode0
DimenFix: A novel meta-dimensionality reduction method for feature preservation—0
Spatio-Temporal Crop Aggregation for Video Representation Learning—0
Privacy-Preserving Federated Deep Clustering based on GAN—0
Compression supports low-dimensional representations of behavior across neural circuits—0
Simultaneous Best Subset Selection and Dimension Reduction via Primal-Dual Iterations—0
Identifying Chemicals Through Dimensionality Reduction—0
Transform Once: Efficient Operator Learning in Frequency DomainCode1
Graph Convolutional Network-based Feature Selection for High-dimensional and Low-sample Size DataCode1
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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