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 311–320 of 3304 papers

TitleStatusHype
Alternating Co-Quantization for Cross-Modal Hashing—0
A Data-Driven and Distributed Approach to Sparse Signal Representation and Recovery—0
Accelerating Text Mining Using Domain-Specific Stop Word Lists—0
A Dashboard to Analysis and Synthesis of Dimensionality Reduction Methods in Remote Sensing—0
Two-stage dimension reduction for noisy high-dimensional images and application to Cryogenic Electron Microscopy—0
A Probabilistic Graph Coupling View of Dimension Reduction—0
A quantitative fusion strategy of stock picking and timing based on Particle Swarm Optimized-Back Propagation Neural Network and Multivariate Gaussian-Hidden Markov Model—0
Accelerating Plug-and-Play Image Reconstruction via Multi-Stage Sketched Gradients—0
A Low Effort Approach to Structured CNN Design Using PCA—0
2D Face Recognition System Based on Selected Gabor Filters and Linear Discriminant Analysis LDA—0
Show:102550
← PrevPage 32 of 331Next →
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