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 2476–2500 of 3304 papers

TitleStatusHype
3D Shape Registration Using Spectral Graph Embedding and Probabilistic Matching—0
3D Structural Phenotype of the Optic Nerve Head at the Intersection of Glaucoma and Myopia - A Key to Improving Glaucoma Diagnosis in Myopic Populations—0
ABACUS: Unsupervised Multivariate Change Detection via Bayesian Source Separation—0
ABC-FL: Anomalous and Benign client Classification in Federated Learning—0
ABID: Angle Based Intrinsic Dimensionality—0
A Bilinear Programming Approach for Multiagent Planning—0
A Bootstrap Method for Error Estimation in Randomized Matrix Multiplication—0
A Brief Survey on Representation Learning based Graph Dimensionality Reduction Techniques—0
Abstraction and Symbolic Execution of Deep Neural Networks with Bayesian Approximation of Hidden Features—0
A canonical correlation-based framework for performance analysis of radio access networks—0
A case study : Influence of Dimension Reduction on regression trees-based Algorithms -Predicting Aeronautics Loads of a Derivative Aircraft—0
A Category Space Approach to Supervised Dimensionality Reduction—0
Accelerated Canonical Polyadic Decomposition by Using Mode Reduction—0
Accelerated partial separable model using dimension-reduced optimization technique for ultra-fast cardiac MRI—0
Accelerated Search for Non-Negative Greedy Sparse Decomposition via Dimensionality Reduction—0
Practical Operator Sketching Framework for Accelerating Iterative Data-Driven Solutions in Inverse Problems—0
Accelerating hyperbolic t-SNE—0
Accelerating hypersonic reentry simulations using deep learning-based hybridization (with guarantees)—0
Accelerating Plug-and-Play Image Reconstruction via Multi-Stage Sketched Gradients—0
Accelerating Text Mining Using Domain-Specific Stop Word Lists—0
Accelerating Vision Transformers Based on Heterogeneous Attention Patterns—0
Accuracy and Privacy Evaluations of Collaborative Data Analysis—0
A Characterization of the Non-Uniqueness of Nonnegative Matrix Factorizations—0
Achieving Fair PCA Using Joint Eigenvalue Decomposition—0
A Class-Based Agreement Model for Generating Accurately Inflected Translations—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