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 321–330 of 3304 papers

TitleStatusHype
2D Face Recognition System Based on Selected Gabor Filters and Linear Discriminant Analysis LDA—0
A Local Similarity-Preserving Framework for Nonlinear Dimensionality Reduction with Neural Networks—0
Adaptive Randomized Dimension Reduction on Massive Data—0
A Qubit-Efficient Hybrid Quantum Encoding Mechanism for Quantum Machine Learning—0
Adaptive physics-informed neural operator for coarse-grained non-equilibrium flows—0
A Lightweight ReLU-Based Feature Fusion for Aerial Scene Classification—0
Co-regularized Multi-view Sparse Reconstruction Embedding for Dimension Reduction—0
A Light weight and Hybrid Deep Learning Model based Online Signature Verification—0
Adaptive Neighboring Selection Algorithm Based on Curvature Prediction in Manifold Learning—0
Accelerating hypersonic reentry simulations using deep learning-based hybridization (with guarantees)—0
Show:102550
← PrevPage 33 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