SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 851–900 of 3304 papers

TitleStatusHype
An Analysis of the t-SNE Algorithm for Data Visualization—0
Benchmarking the Effectiveness of Classification Algorithms and SVM Kernels for Dry Beans—0
Belted and Ensembled Neural Network for Linear and Nonlinear Sufficient Dimension Reduction—0
Exact Cluster Recovery via Classical Multidimensional Scaling—0
Beam-Space MIMO Radar for Joint Communication and Sensing with OTFS Modulation—0
BDEC:Brain Deep Embedded Clustering model—0
Analyzing movies to predict their commercial viability for producers—0
A Discussion On the Validity of Manifold Learning—0
A bi-partite generative model framework for analyzing and simulating large scale multiple discrete-continuous travel behaviour data—0
Bayesian optimization for mixed variables using an adaptive dimension reduction process: applications to aircraft design—0
Bayesian nonparametric Principal Component Analysis—0
ANALYTiC: Understanding Decision Boundaries and Dimensionality Reduction in Machine Learning—0
A dimensionality reduction technique based on the Gromov-Wasserstein distance—0
Bayesian neural networks and dimensionality reduction—0
Bayesian model and dimension reduction for uncertainty propagation: applications in random media—0
Bayesian Learning of Parameterised Quantum Circuits—0
Analytic Bilinear Appearance Subspace Construction for Modeling Image Irradiance under Natural Illumination and Non-Lambertian Reflectance—0
A Dimensionality Reduction Method for Finding Least Favorable Priors with a Focus on Bregman Divergence—0
A cognitive based Intrusion detection system—0
Bayesian Learning of Dynamic Multilayer Networks—0
Analysis of Evolving Cortical Neuronal Networks Using Visual Informatics—0
Bayesian inverse regression for dimension reduction with small datasets—0
Bayesian Inverse Problems with Conditional Sinkhorn Generative Adversarial Networks in Least Volume Latent Spaces—0
Analysis of Cellular Feature Differences of Astrocytomas with Distinct Mutational Profiles Using Digitized Histopathology Images—0
Bayesian Inference on Matrix Manifolds for Linear Dimensionality Reduction—0
Bayesian full waveform inversion with sequential surrogate model refinement—0
Analysis and Visualization of Deep Neural Networks in Device-Free Wi-Fi Indoor Localization—0
Bayesian Exponential Family PCA—0
Bayesian Data Sketching for Varying Coefficient Regression Models—0
Analysis and mining of low-carbon and energy-saving tourism data characteristics based on machine learning algorithm—0
A Dimensionality Reduction Approach for Convolutional Neural Networks—0
Bayesian Compressed Regression—0
Analysing race and sex bias in brain age prediction—0
Bayesian Calibration for Activity Based Models—0
Analyse en Composante Principale pour l'extraction des i-vecteurs en v\'erification du locuteur (Principal Component Analysis for i-vector extraction in speaker verification.) [in French]—0
A determinantal point process for column subset selection—0
A witness function based construction of discriminative models using Hermite polynomials—0
An Algorithmic Information Calculus for Causal Discovery and Reprogramming Systems—0
A description length approach to determining the number of k-means clusters—0
A clustering adaptive Gaussian process regression method: response patterns based real-time prediction for nonlinear solid mechanics problems—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
Feature Clock: High-Dimensional Effects in Two-Dimensional Plots—0
A Wavelet Diffusion GAN for Image Super-Resolution—0
A Wasserstein perspective of Vanilla GANs—0
An Algorithm and Heuristic based on Normalized Mutual Information for Dimensionality Reduction and Classification of Hyperspectral images—0
A Visual Interaction Framework for Dimensionality Reduction Based Data Exploration—0
A Visual Analytics Framework for Reviewing Multivariate Time-Series Data with Dimensionality Reduction—0
A-DenseUNet: Adaptive Densely Connected UNet for Polyp Segmentation in Colonoscopy Images with Atrous Convolution—0
AVIDA: Alternating method for Visualizing and Integrating Data—0
A VAE-Bayesian Deep Learning Scheme for Solar Generation Forecasting based on Dimensionality Reduction—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