SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 2301–2350 of 3304 papers

TitleStatusHype
Deep Embedded SOM: Joint Representation Learning and Self-OrganizationCode0
A Robust Approach for Securing Audio Classification Against Adversarial Attacks—0
Analysis and Visualization of Deep Neural Networks in Device-Free Wi-Fi Indoor Localization—0
Local Deep-Feature Alignment for Unsupervised Dimension Reduction—0
SCANN: Synthesis of Compact and Accurate Neural Networks—0
Privacy-Enhancing Context Authentication from Location-Sensitive Data—0
Multi-stage Antenna Selection for Adaptive Beamforming in MIMO Arrays—0
Fast Single Image Dehazing via Multilevel Wavelet Transform based OptimizationCode0
Dimensionality Reduction of Complex Metastable Systems via Kernel Embeddings of Transition ManifoldsCode0
Kernel methods for detecting coherent structures in dynamical data—0
PL-NMF: Parallel Locality-Optimized Non-negative Matrix Factorization—0
Estimation of Cross-Sectional Dependence in Large Panels—0
A framework for streamlined statistical prediction using topic models—0
GraphTSNE: A Visualization Technique for Graph-Structured DataCode0
Self-Paced Probabilistic Principal Component Analysis for Data with Outliers—0
Restricted Isometry Property under High Correlations—0
Beyond the Nucleus: Cytoplasmic Dominance in Follicular Thyroid Carcinoma Detection Using Single-Cell Raman Imaging Across Multiple DevicesCode0
Analyzing Dynamical Brain Functional Connectivity As Trajectories on Space of Covariance MatricesCode0
Simultaneous Spectral-Spatial Feature Selection and Extraction for Hyperspectral Images—0
Parametrization of stochastic inputs using generative adversarial networks with application in geology—0
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 Classifier—0
Co-regularized Multi-view Sparse Reconstruction Embedding for Dimension Reduction—0
Information Theoretic Feature Transformation Learning for Brain Interfaces—0
Smoothing Nonlinear Variational Objectives with Sequential Monte Carlo—0
Gene Expression based Survival Prediction for Cancer Patients: A Topic Modeling Approach—0
Interactions between Representation Learning and Supervision—0
CUR Decompositions, Approximations, and Perturbations—0
Aggregated Deep Local Features for Remote Sensing Image Retrieval—0
Individualized Multilayer Tensor Learning with An Application in Imaging Analysis—0
Latent Simplex Position Model: High Dimensional Multi-view Clustering with Uncertainty Quantification—0
On the Computation and Applications of Large Dense Partial Correlation Networks—0
Deep Feature Selection using a Teacher-Student NetworkCode0
Multi-Stage Fault Warning for Large Electric Grids Using Anomaly Detection and Machine Learning—0
DysLexML: Screening Tool for Dyslexia Using Machine Learning—0
Reducing the dimensionality of data using tempered distributionsCode0
A Grid-based Method for Removing Overlaps of Dimensionality Reduction Scatterplot LayoutsCode0
Deep Random Splines for Point Process Intensity Estimation of Neural Population DataCode0
GraphVite: A High-Performance CPU-GPU Hybrid System for Node EmbeddingCode0
Multi-Criteria Dimensionality Reduction with Applications to FairnessCode0
Efficient Contextual Representation Learning Without Softmax Layer—0
High-dimensional Bayesian optimization using low-dimensional feature spacesCode0
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
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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