SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

Showing 23012350 of 3304 papers

TitleStatusHype
Simultaneous Spectral-Spatial Feature Selection and Extraction for Hyperspectral Images0
Parametrization of stochastic inputs using generative adversarial networks with application in geology0
Is 'Unsupervised Learning' a Misconceived Term?0
Online Convex Matrix Factorization with Representative RegionsCode0
Building an Efficient Intrusion Detection System Based on Feature Selection and Ensemble Classifier0
Co-regularized Multi-view Sparse Reconstruction Embedding for Dimension Reduction0
Information Theoretic Feature Transformation Learning for Brain Interfaces0
Smoothing Nonlinear Variational Objectives with Sequential Monte Carlo0
Interactions between Representation Learning and Supervision0
Gene Expression based Survival Prediction for Cancer Patients: A Topic Modeling Approach0
CUR Decompositions, Approximations, and Perturbations0
Aggregated Deep Local Features for Remote Sensing Image Retrieval0
Latent Simplex Position Model: High Dimensional Multi-view Clustering with Uncertainty Quantification0
Individualized Multilayer Tensor Learning with An Application in Imaging Analysis0
Deep Feature Selection using a Teacher-Student NetworkCode0
On the Computation and Applications of Large Dense Partial Correlation Networks0
Multi-Stage Fault Warning for Large Electric Grids Using Anomaly Detection and Machine Learning0
DysLexML: Screening Tool for Dyslexia Using Machine Learning0
Reducing the dimensionality of data using tempered distributionsCode0
A Grid-based Method for Removing Overlaps of Dimensionality Reduction Scatterplot LayoutsCode0
Learning the dynamics of technical trading strategiesCode1
Deep Random Splines for Point Process Intensity Estimation of Neural Population DataCode0
GraphVite: A High-Performance CPU-GPU Hybrid System for Node EmbeddingCode0
Efficient Contextual Representation Learning Without Softmax Layer0
Multi-Criteria Dimensionality Reduction with Applications to FairnessCode0
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 Ranking0
A Review, Framework and R toolkit for Exploring, Evaluating, and Comparing Visualizations0
Deep Learning Multidimensional Projections0
Noisy multi-label semi-supervised dimensionality reduction0
Exploring Language Similarities with Dimensionality Reduction TechniqueCode0
Unsupervised shape and motion analysis of 3822 cardiac 4D MRIs of UK Biobank0
Deep learning approach based on dimensionality reduction for designing electromagnetic nanostructures0
Riemannian joint dimensionality reduction and dictionary learning on symmetric positive definite manifold0
ReStoCNet: Residual Stochastic Binary Convolutional Spiking Neural Network for Memory-Efficient Neuromorphic Computing0
Machine Learning With Feature Selection Using Principal Component Analysis for Malware Detection: A Case Study0
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 improvement0
Can Genetic Programming Do Manifold Learning Too?0
License Plate Recognition with Compressive Sensing Based Feature Extraction0
Principal Model Analysis Based on Partial Least Squares0
Riemannian optimization with a preconditioning scheme on the generalized Stiefel manifold0
Minimum description length as an objective function for non-negative matrix factorization0
A Tangent Distance Preserving Dimensionality Reduction Algorithm0
Higher-order Count Sketch: Dimensionality Reduction That Retains Efficient Tensor Operations0
Distinguishing between Normal and Cancer Cells Using Autoencoder Node Saliency0
Distributionally Robust and Multi-Objective Nonnegative Matrix Factorization0
Throttling Malware Families in 2DCode0
A Deep Learning Framework for Assessing Physical Rehabilitation ExercisesCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy90.9Unverified
2tSNEClassification Accuracy51.5Unverified
3IVISClassification Accuracy46.6Unverified
4UMAPClassification Accuracy41.3Unverified
#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy71.1Unverified
2QSClassification Accuracy68Unverified