SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1671–1680 of 3304 papers

TitleStatusHype
Efficient Quantum Convolutional Neural Networks for Image Classification: Overcoming Hardware Constraints—0
Efficient Sketching Algorithm for Sparse Binary Data—0
Efficient Sparse PCA via Block-Diagonalization—0
Efficient Tensor Contraction via Fast Count Sketch—0
Efficient Text Classification Using Tree-structured Multi-linear Principal Component Analysis—0
Eigen-GNN: A Graph Structure Preserving Plug-in for GNNs—0
EigenGS Representation: From Eigenspace to Gaussian Image Space—0
ELA: Efficient Local Attention for Deep Convolutional Neural Networks—0
Elastic deep autoencoder for text embedding clustering by an improved graph regularization—0
Electrical Grid Anomaly Detection via Tensor Decomposition—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