SOTAVerified

Dimensionality Reduction

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

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Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 2876–2900 of 3304 papers

TitleStatusHype
Ellipsoid fitting with the Cayley transformCode0
Interpretable Visualization and Higher-Order Dimension Reduction for ECoG DataCode0
Self Organizing Nebulous Growths for Robust and Incremental Data VisualizationCode0
A method to integrate and classify normal distributionsCode0
Interpreting LSTM Prediction on Solar Flare Eruption with Time-series ClusteringCode0
ClusterGraph: a new tool for visualization and compression of multidimensional dataCode0
MURAL: An Unsupervised Random Forest-Based Embedding for Electronic Health Record DataCode0
ENS-t-SNE: Embedding Neighborhoods Simultaneously t-SNECode0
Intrinsic Dimensionality Estimation within Tight Localities: A Theoretical and Experimental AnalysisCode0
MXNet: A Flexible and Efficient Machine Learning Library for Heterogeneous Distributed SystemsCode0
Introducing user-prescribed constraints in Markov chains for nonlinear dimensionality reductionCode0
Introduction to Facial Micro Expressions Analysis Using Color and Depth Images: A Matlab Coding Approach (Second Edition, 2023)Code0
Inverse Kernel DecompositionCode0
Empirical Evaluation of Pre-trained Transformers for Human-Level NLP: The Role of Sample Size and DimensionalityCode0
Empirical likelihood approach for high-dimensional moment restrictions with dependent dataCode0
Mycorrhiza: Genotype Assignment usingPhylogenetic NetworksCode0
Theoretical Error Performance Analysis for Variational Quantum Circuit Based Functional RegressionCode0
Emulating Spatio-Temporal Realizations of Three-Dimensional Isotropic Turbulence via Deep Sequence Learning ModelsCode0
Invertible Manifold Learning for Dimension ReductionCode0
A Clustering Framework for Residential Electric Demand ProfilesCode0
Enabling stratified sampling in high dimensions via nonlinear dimensionality reductionCode0
Accelerated Stochastic Power IterationCode0
Investigating Privacy Leakage in Dimensionality Reduction Methods via Reconstruction AttackCode0
Investigating Shallow and Deep Learning Techniques for Emotion Classification in Short Persian TextsCode0
Enhanced Expressive Power and Fast Training of Neural Networks by Random ProjectionsCode0
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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