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 1101–1150 of 3304 papers

TitleStatusHype
Detection and tracking of gas plumes in LWIR hyperspectral video sequence data—0
A theoretical contribution to the fast implementation of null linear discriminant analysis method using random matrix multiplication with scatter matrices—0
A Masked Pruning Approach for Dimensionality Reduction in Communication-Efficient Federated Learning Systems—0
A Data Quarantine Model to Secure Data in Edge Computing—0
Detection and Identification Accuracy of PCA-Accelerated Real-Time Processing of Hyperspectral Imagery—0
A Theoretical Analysis of Noisy Sparse Subspace Clustering on Dimensionality-Reduced Data—0
Detection and Evaluation of Clusters within Sequential Data—0
Detecting the Trend in Musical Taste over the Decade -- A Novel Feature Extraction Algorithm to Classify Musical Content with Simple Features—0
A Tangent Distance Preserving Dimensionality Reduction Algorithm—0
A Machine-Learning-Aided Visual Analysis Workflow for Investigating Air Pollution Data—0
Detecting single-trial EEG evoked potential using a wavelet domain linear mixed model: application to error potentials classification—0
A Tale of Two Bases: Local-Nonlocal Regularization on Image Patches with Convolution Framelets—0
Detecting Changes in Asset Co-Movement Using the Autoencoder Reconstruction Ratio—0
A Systematic Study of Semantic Vector Space Model Parameters—0
Alternative Channel Charting Techniques in Cellular Wireless Communications—0
A data-driven approach for multiscale elliptic PDEs with random coefficients based on intrinsic dimension reduction—0
Accelerating Vision Transformers Based on Heterogeneous Attention Patterns—0
Detailed Investigation of Deep Features with Sparse Representation and Dimensionality Reduction in CBIR: A Comparative Study—0
Design of Recognition and Evaluation System for Table Tennis Players' Motor Skills Based on Artificial Intelligence—0
Design of Explainability Module with Experts in the Loop for Visualization and Dynamic Adjustment of Continual Learning—0
Asymptotic Generalization Bound of Fisher's Linear Discriminant Analysis—0
Alternating Diffusion Map Based Fusion of Multimodal Brain Connectivity Networks for IQ Prediction—0
A Symmetric Rank-one Quasi Newton Method for Non-negative Matrix Factorization—0
Depth separation for reduced deep networks in nonlinear model reduction: Distilling shock waves in nonlinear hyperbolic problems—0
Density-based Isometric Mapping—0
Alternating Co-Quantization for Cross-Modal Hashing—0
A Data-Driven and Distributed Approach to Sparse Signal Representation and Recovery—0
Denoising VAE as an Explainable Feature Reduction and Diagnostic Pipeline for Autism Based on Resting state fMRI—0
DenDrift: A Drift-Aware Algorithm for Host Profiling—0
Demystifying Embedding Spaces using Large Language Models—0
Demonstrating Superresolution in Radar Range Estimation Using a Denoising Autoencoder—0
A Survey on Design-space Dimensionality Reduction Methods for Shape Optimization—0
Demixed Principal Component Analysis—0
A Survey on Archetypal Analysis—0
DEMEA: Deep Mesh Autoencoders for Non-Rigidly Deforming Objects—0
Delamination prediction in composite panels using unsupervised-feature learning methods with wavelet-enhanced guided wave representations—0
A survey of unsupervised learning methods for high-dimensional uncertainty quantification in black-box-type problems—0
A Dashboard to Analysis and Synthesis of Dimensionality Reduction Methods in Remote Sensing—0
Accelerating Text Mining Using Domain-Specific Stop Word Lists—0
Two-stage dimension reduction for noisy high-dimensional images and application to Cryogenic Electron Microscopy—0
Compressive Mahalanobis Metric Learning Adapts to Intrinsic Dimension—0
Defining Reference Sequences for Nocardia Species by Similarity and Clustering Analyses of 16S rRNA Gene Sequence Data—0
A survey of dimensionality reduction techniques based on random projection—0
A survey of dimensionality reduction techniques—0
Deep Variational Sufficient Dimensionality Reduction—0
Deep Variational Multivariate Information Bottleneck -- A Framework for Variational Losses—0
A Supervised Tensor Dimension Reduction-Based Prognostics Model for Applications with Incomplete Imaging Data—0
Deep Triphone Embedding Improves Phoneme Recognition—0
Deep topic modeling by multilayer bootstrap network and lasso—0
A Supervised Screening and Regularized Factor-Based Method for Time Series Forecasting—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