SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 2751–2800 of 3304 papers

TitleStatusHype
A Review, Framework and R toolkit for Exploring, Evaluating, and Comparing Visualizations—0
A review of unsupervised learning in astronomy—0
A Robust and Efficient Boundary Point Detection Method by Measuring Local Direction Dispersion—0
A Robust Approach for Securing Audio Classification Against Adversarial Attacks—0
Artificial Intelligence and Dimensionality Reduction: Tools for approaching future communications—0
A selective review of sufficient dimension reduction for multivariate response regression—0
A Semiparametric Approach to Interpretable Machine Learning—0
A Semi-supervised Spatial Spectral Regularized Manifold Local Scaling Cut With HGF for Dimensionality Reduction of Hyperspectral Images—0
A Simple and Effective Approach to Robust Unsupervised Bilingual Dictionary Induction—0
A simple coding for cross-domain matching with dimension reduction via spectral graph embedding—0
A Spatial Mapping Algorithm with Applications in Deep Learning-Based Structure Classification—0
Split Semantic Detection in Sandplay Images—0
A Stable Measure for Conditional Periodicity of Time Series using Persistent Homology—0
A Statistical Approach to Increase Classification Accuracy in Supervised Learning Algorithms—0
Asteroids co-orbital motion classification based on Machine Learning—0
AstroM^3: A self-supervised multimodal model for astronomy—0
A Study of Feature Selection and Extraction Algorithms for Cancer Subtype Prediction—0
A study of semantic augmentation of word embeddings for extractive summarization—0
A study of the classification of low-dimensional data with supervised manifold learning—0
The Effects of Spectral Dimensionality Reduction on Hyperspectral Pixel Classification: A Case Study—0
A Subspace-based Approach for Dimensionality Reduction and Important Variable Selection—0
A Supervised Geometry-Aware Mapping Approach for Classification of Hyperspectral Images—0
A Supervised Screening and Regularized Factor-Based Method for Time Series Forecasting—0
A Supervised Tensor Dimension Reduction-Based Prognostics Model for Applications with Incomplete Imaging Data—0
A survey of dimensionality reduction techniques—0
A survey of dimensionality reduction techniques based on random projection—0
A survey of unsupervised learning methods for high-dimensional uncertainty quantification in black-box-type problems—0
A Survey on Archetypal Analysis—0
A Survey on Design-space Dimensionality Reduction Methods for Shape Optimization—0
A Symmetric Rank-one Quasi Newton Method for Non-negative Matrix Factorization—0
Asymptotic Generalization Bound of Fisher's Linear Discriminant Analysis—0
A Systematic Study of Semantic Vector Space Model Parameters—0
A Tale of Two Bases: Local-Nonlocal Regularization on Image Patches with Convolution Framelets—0
A Tangent Distance Preserving Dimensionality Reduction Algorithm—0
A Theoretical Analysis of Noisy Sparse Subspace Clustering on Dimensionality-Reduced Data—0
A theoretical contribution to the fast implementation of null linear discriminant analysis method using random matrix multiplication with scatter matrices—0
A topological classifier to characterize brain states: When shape matters more than variance—0
A Topological "Reading" Lesson: Classification of MNIST using TDA—0
A Trace Lasso Regularized L1-norm Graph Cut for Highly Correlated Noisy Hyperspectral Image—0
A t-SNE Based Classification Approach to Compositional Microbiome Data—0
Attention-based Supply-Demand Prediction for Autonomous Vehicles—0
Attention is all you need for Videos: Self-attention based Video Summarization using Universal Transformers—0
Attention or memory? Neurointerpretable agents in space and time—0
A Tutorial on Distance Metric Learning: Mathematical Foundations, Algorithms, Experimental Analysis, Prospects and Challenges (with Appendices on Mathematical Background and Detailed Algorithms Explanation)—0
A Two-Stage Dual-Path Framework for Text Tampering Detection and Recognition—0
A Two-Stage Federated Learning Approach for Industrial Prognostics Using Large-Scale High-Dimensional Signals—0
Audio Visual Speech Recognition using Deep Recurrent Neural Networks—0
Augment on Manifold: Mixup Regularization with UMAP—0
A Unified Framework for Optimization-Based Graph Coarsening—0
A Unifying Family of Data-Adaptive Partitioning Algorithms—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