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 1151–1175 of 3304 papers

TitleStatusHype
Enhancing the conformal predictability of context-aware recommendation systems by using Deep Autoencoders—0
Enhancing UAV Path Planning Efficiency Through Accelerated Learning—0
EnsembleNTLDetect: An Intelligent Framework for Electricity Theft Detection in Smart Grid—0
Ensembles of Classifiers based on Dimensionality Reduction—0
Entangled Kernels -- Beyond Separability—0
Entangled Mean Estimation in High-Dimensions—0
A new set of cluster driven composite development indicators—0
Entropy-Isomap: Manifold Learning for High-dimensional Dynamic Processes—0
A New Spatio-Spectral Morphological Segmentation For Multi-Spectral Remote-Sensing Images—0
An enhanced Teaching-Learning-Based Optimization (TLBO) with Grey Wolf Optimizer (GWO) for text feature selection and clustering—0
Efficient NTK using Dimensionality Reduction—0
Error Metrics for Learning Reliable Manifolds from Streaming Data—0
ESCAPED: Efficient Secure and Private Dot Product Framework for Kernel-based Machine Learning Algorithms with Applications in Healthcare—0
ESPACE: Dimensionality Reduction of Activations for Model Compression—0
Estimates on the domain of validity for Lyapunov-Schmidt reduction—0
Estimating a Manifold from a Tangent Bundle Learner—0
Estimating Conditional Average Treatment Effects via Sufficient Representation Learning—0
Estimating covariance and precision matrices along subspaces—0
Adversarial Vulnerability as a Consequence of On-Manifold Inseparibility—0
Estimating Model Uncertainty of Neural Networks in Sparse Information Form—0
Estimating Model Uncertainty of Neural Network in Sparse Information Form—0
Estimation of Cross-Sectional Dependence in Large Panels—0
Estimation of Dimensions Contributing to Detected Anomalies with Variational Autoencoders—0
Evaluating deep variational autoencoders trained on pan-cancer gene expression—0
Efficient Nearest Neighbor based Uncertainty Estimation for Natural Language Processing Tasks—0
Show:102550
← PrevPage 47 of 133Next →
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