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 3271–3280 of 3304 papers

TitleStatusHype
Efficiently Computing Similarities to Private Datasets—0
Efficient Malware Detection with Optimized Learning on High-Dimensional Features—0
Efficient Nearest Neighbor based Uncertainty Estimation for Natural Language Processing Tasks—0
Efficient NTK using Dimensionality Reduction—0
Efficient Optimization for Discriminative Latent Class Models—0
Efficient Principal Subspace Projection of Streaming Data Through Fast Similarity Matching—0
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
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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