SOTAVerified

Dimensionality Reduction

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

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Papers

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Showing 951–1000 of 3304 papers

TitleStatusHype
CAMEL: Curvature-Augmented Manifold Embedding and Learning—0
Comparative Studies of Unsupervised and Supervised Learning Methods based on Multimedia Applications—0
Graph-based Extreme Feature Selection for Multi-class Classification Tasks—0
Large Deviations for Accelerating Neural Networks Training—0
In search of the most efficient and memory-saving visualization of high dimensional data—0
Wasserstein Projection Pursuit of Non-Gaussian Signals—0
Small Sample Hyperspectral Image Classification Based on the Random Patches Network and Recursive FilteringCode0
Deep Kernel Principal Component Analysis for Multi-level Feature LearningCode0
nSimplex Zen: A Novel Dimensionality Reduction for Euclidean and Hilbert SpacesCode0
DC4L: Distribution Shift Recovery via Data-Driven Control for Deep Learning ModelsCode0
Image Reconstruction via Deep Image Prior SubspacesCode0
Novel Epileptic Seizure Detection Techniques and their Empirical Analysis—0
PAC-Bayesian Generalization Bounds for Adversarial Generative ModelsCode0
Linearized Wasserstein dimensionality reduction with approximation guarantees—0
Kernelized Diffusion mapsCode1
Low-dimensional Data-based Surrogate Model of a Continuum-mechanical Musculoskeletal System Based on Non-intrusive Model Order Reduction—0
Sparse Dimensionality Reduction Revisited—0
Mixed Multi-Model Semantic Interaction for Graph-based Narrative Visualizations—0
Dimension Reduction and MARSCode0
Dimension reduction and redundancy removal through successive Schmidt decompositions—0
A Systematic Performance Analysis of Deep Perceptual Loss Networks: Breaking Transfer Learning ConventionsCode0
Decentralized Riemannian Algorithm for Nonconvex Minimax Problems—0
Monge, Bregman and Occam: Interpretable Optimal Transport in High-Dimensions with Feature-Sparse Maps—0
LiteVR: Interpretable and Lightweight Cybersickness Detection using Explainable AI—0
Learning Topology-Preserving Data RepresentationsCode1
Supporting Safety Analysis of Image-processing DNNs through Clustering-based Approaches—0
Master's Thesis: Out-of-distribution Detection with Energy-based ModelsCode0
SparCA: Sparse Compressed Agglomeration for Feature Extraction and Dimensionality ReductionCode0
Automatic Debiased Estimation with Machine Learning-Generated Regressors—0
A predictive physics-aware hybrid reduced order model for reacting flows—0
Capacity Analysis of Vector Symbolic Architectures—0
Online Kernel Sliced Inverse Regression—0
Federated Sufficient Dimension Reduction Through High-Dimensional Sparse Sliced Inverse Regression—0
Information loss from dimensionality reduction in 5D-Gaussian spectral data—0
Using Topological Data Analysis to classify Encrypted Bits—0
DR-WLC: Dimensionality Reduction cognition for object detection and pose estimation by Watching, Learning and CheckingCode0
Dual-sPLS: a family of Dual Sparse Partial Least Squares regressions for feature selection and prediction with tunable sparsity; evaluation on simulated and near-infrared (NIR) dataCode0
Segmenting thalamic nuclei from manifold projections of multi-contrast MRI—0
Fair and skill-diverse student group formation via constrained k-way graph partitioning—0
ImMesh: An Immediate LiDAR Localization and Meshing FrameworkCode2
Fast conformational clustering of extensive molecular dynamics simulation dataCode1
Fair Recommendation by Geometric Interpretation and Analysis of Matrix Factorization—0
Latent Autoregressive Source SeparationCode1
Topologically Regularized Data EmbeddingsCode0
Principal Component Analysis in Space FormsCode1
EPR-Net: Constructing non-equilibrium potential landscape via a variational force projection formulationCode0
Reduced Deep Convolutional Activation Features (R-DeCAF) in Histopathology Images to Improve the Classification Performance for Breast Cancer Diagnosis—0
KIDS: kinematics-based (in)activity detection and segmentation in a sleep case study—0
ClusTop: An unsupervised and integrated text clustering and topic extraction framework—0
Unsupervised Acoustic Scene Mapping Based on Acoustic Features and 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