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Dimensionality Reduction

Dimensionality reduction is the task of reducing the dimensionality of a dataset.

( Image credit: openTSNE )

Papers

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Showing 2326–2350 of 3304 papers

TitleStatusHype
High-dimensional Bayesian optimization using low-dimensional feature spacesCode0
Deep active subspaces - a scalable method for high-dimensional uncertainty propagationCode1
Ordinal Distance Metric Learning with MDS for Image Ranking—0
A Review, Framework and R toolkit for Exploring, Evaluating, and Comparing Visualizations—0
Deep Learning Multidimensional Projections—0
Noisy multi-label semi-supervised dimensionality reduction—0
Exploring Language Similarities with Dimensionality Reduction TechniqueCode0
Unsupervised shape and motion analysis of 3822 cardiac 4D MRIs of UK Biobank—0
Deep learning approach based on dimensionality reduction for designing electromagnetic nanostructures—0
Riemannian joint dimensionality reduction and dictionary learning on symmetric positive definite manifold—0
ReStoCNet: Residual Stochastic Binary Convolutional Spiking Neural Network for Memory-Efficient Neuromorphic Computing—0
Machine Learning With Feature Selection Using Principal Component Analysis for Malware Detection: A Case Study—0
ELKI: A large open-source library for data analysis - ELKI Release 0.7.5 "Heidelberg"—0
Distance metric learning based on structural neighborhoods for dimensionality reduction and classification performance improvement—0
Can Genetic Programming Do Manifold Learning Too?—0
License Plate Recognition with Compressive Sensing Based Feature Extraction—0
Principal Model Analysis Based on Partial Least Squares—0
Riemannian optimization with a preconditioning scheme on the generalized Stiefel manifold—0
Minimum description length as an objective function for non-negative matrix factorization—0
A Tangent Distance Preserving Dimensionality Reduction Algorithm—0
Higher-order Count Sketch: Dimensionality Reduction That Retains Efficient Tensor Operations—0
Distinguishing between Normal and Cancer Cells Using Autoencoder Node Saliency—0
Distributionally Robust and Multi-Objective Nonnegative Matrix Factorization—0
Throttling Malware Families in 2DCode0
A Deep Learning Framework for Assessing Physical Rehabilitation ExercisesCode0
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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