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 3151–3200 of 3304 papers

TitleStatusHype
Small Sample Hyperspectral Image Classification Based on the Random Patches Network and Recursive FilteringCode0
Dimensionality Reduction and Nearest Neighbors for Improving Out-of-Distribution Detection in Medical Image SegmentationCode0
Adaptive Mixtures of Factor AnalyzersCode0
[Re] Explaining Groups of Points in Low-Dimensional RepresentationsCode0
Gaussian Process Latent Variable Model Factorization for Context-aware Recommender SystemsCode0
Refusal Behavior in Large Language Models: A Nonlinear PerspectiveCode0
Curvature Augmented Manifold Embedding and LearningCode0
Branching embedding: A heuristic dimensionality reduction algorithm based on hierarchical clusteringCode0
Regional Expected Improvement for Efficient Trust Region Selection in High-Dimensional Bayesian OptimizationCode0
VERA: Generating Visual Explanations of Two-Dimensional Embeddings via Region AnnotationCode0
On the Estimation of Entropy in the FastICA AlgorithmCode0
Supervised multiway factorizationCode0
SMSSVD - SubMatrix Selection Singular Value DecompositionCode0
Local Explanation of Dimensionality ReductionCode0
On the Inherent Robustness of One-Stage Object Detection against Out-of-Distribution DataCode0
Generalized Image Reconstruction over T-AlgebraCode0
Data-Driven Socio-Economic Deprivation Prediction via Dimensionality Reduction: The Power of Diffusion MapsCode0
Generalized Penalty for Circular Coordinate RepresentationCode0
On the Noise Sensitivity of the Randomized SVDCode0
Generalized probabilistic canonical correlation analysis for multi-modal data integration with full or partial observationsCode0
Supervised Quadratic Feature Analysis: Information Geometry Approach for Dimensionality ReductionCode0
Solar Flare Forecast: A Comparative Analysis of Machine Learning Algorithms for Solar Flare Class PredictionCode0
Supervised Stochastic Neighbor Embedding Using Contrastive LearningCode0
Solving ARC visual analogies with neural embeddings and vector arithmetic: A generalized methodCode0
Solving Interpretable Kernel Dimension ReductionCode0
Cross-Temporal Spectrogram Autoencoder (CTSAE): Unsupervised Dimensionality Reduction for Clustering Gravitational Wave GlitchesCode0
CoverBLIP: accelerated and scalable iterative matched-filtering for Magnetic Resonance Fingerprint reconstructionCode0
Affective Manifolds: Modeling Machine's Mind to Like, Dislike, Enjoy, Suffer, Worry, Fear, and Feel Like A HumanCode0
Bounds on Representation-Induced Confounding Bias for Treatment Effect EstimationCode0
Locally Linear Image Structural Embedding for Image Structure Manifold LearningCode0
Solving Large-Scale Sparse PCA to Certifiable (Near) OptimalityCode0
Local manifold learning and its link to domain-based physics knowledgeCode0
Solving NMF with smoothness and sparsity constraints using PALMCode0
Genomic data analysis in tree spacesCode0
A Linearly Convergent Algorithm for Distributed Principal Component AnalysisCode0
An evaluation framework for dimensionality reduction through sectional curvatureCode0
On the use of the Gram matrix for multivariate functional principal components analysisCode0
Long-term Conversation Analysis: Exploring Utility and PrivacyCode0
Supervised Dimensionality Reduction for Big DataCode0
Analyzing scRNA-seq data by CCP-assisted UMAP and t-SNECode0
Tuning-Free Structured Sparse PCA via Deep Unfolding NetworksCode0
SOM-VAE: Interpretable Discrete Representation Learning on Time SeriesCode0
On the Whitney near extension problem, BMO, alignment of data, best approximation in algebraic geometry, manifold learning and their beautiful connections: A modern treatmentCode0
A Systematic Performance Analysis of Deep Perceptual Loss Networks: Breaking Transfer Learning ConventionsCode0
Decomposing feature-level variation with Covariate Gaussian Process Latent Variable ModelsCode0
Adversarial Robustness of VAEs across Intersectional SubgroupsCode0
Covariance-free Partial Least Squares: An Incremental Dimensionality Reduction MethodCode0
Supervision and Source Domain Impact on Representation Learning: A Histopathology Case StudyCode0
ADAGIO: Fast Data-aware Near-Isometric Linear EmbeddingsCode0
Representation Learning with Deconvolution for Multivariate Time Series Classification and VisualizationCode0
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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