SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

Showing 801850 of 3304 papers

TitleStatusHype
Dimensionality Reduction using Similarity-induced EmbeddingsCode0
Dimensionality reduction of neuronal degeneracy reveals two interfering physiological mechanismsCode0
Dimensionality reduction, regularization, and generalization in overparameterized regressionsCode0
Deep Learning with Nonparametric ClusteringCode0
Deep Linear Discriminant AnalysisCode0
A Statistical View of Column Subset SelectionCode0
Roweis Discriminant Analysis: A Generalized Subspace Learning MethodCode0
Dimension-reduced Optimization of Multi-zone Thermostatically Controlled LoadsCode0
Safe squeezing for antisparse codingCode0
Encoding large information structures in linear algebra and statistical modelsCode0
Dimensionality Reduction for Improving Out-of-Distribution Detection in Medical Image SegmentationCode0
Weight Matrix Dimensionality Reduction in Deep Learning via Kronecker Multi-layer ArchitecturesCode0
DeepNuParc: A Novel Deep Clustering Framework for Fine-scale Parcellation of Brain Nuclei Using Diffusion MRI TractographyCode0
Scaling Gaussian Process Regression with DerivativesCode0
Dimensionality Reduction and (Bucket) Ranking: a Mass Transportation ApproachCode0
Bidirectional deep-readout echo state networksCode0
Dimensionality Reduction for Binary Data through the Projection of Natural ParametersCode0
Self Organizing Nebulous Growths for Robust and Incremental Data VisualizationCode0
Semantic Relatedness Based Re-ranker for Text SpottingCode0
Deep Symmetric Autoencoders from the Eckart-Young-Schmidt PerspectiveCode0
Deep Temporal Clustering : Fully Unsupervised Learning of Time-Domain FeaturesCode0
Deep Temporal Clustering: Fully unsupervised learning of time-domain featuresCode0
Adaptive Weighted Nonnegative Matrix Factorization for Robust Feature RepresentationCode0
Sifting Common Information from Many VariablesCode0
Dimensionality Reduction Meets Message Passing for Graph Node EmbeddingsCode0
Similarity encoding for learning with dirty categorical variablesCode0
Differentiable VQ-VAE's for Robust White Matter Streamline EncodingsCode0
DiffRed: Dimensionality Reduction guided by stable rankCode0
Simple and Effective Dimensionality Reduction for Word EmbeddingsCode0
Degradation Modeling and Prognostic Analysis Under Unknown Failure ModesCode0
Principal component analysis balancing prediction and approximation accuracy for spatial dataCode0
Small Sample Hyperspectral Image Classification Based on the Random Patches Network and Recursive FilteringCode0
Data-Driven Socio-Economic Deprivation Prediction via Dimensionality Reduction: The Power of Diffusion MapsCode0
Demixed principal component analysis of population activity in higher cortical areas reveals independent representation of task parametersCode0
ALPCAHUS: Subspace Clustering for Heteroscedastic DataCode0
Solving Interpretable Kernel Dimension ReductionCode0
Dimensionality Collapse: Optimal Measurement Selection for Low-Error Infinite-Horizon ForecastingCode0
Dimension reduction methods, persistent homology and machine learning for EEG signal analysis of Interictal Epileptic DischargesCode0
A Survey on Multi-Task LearningCode0
Sparse and Functional Principal Components AnalysisCode0
Earthmover-based manifold learning for analyzing molecular conformation spacesCode0
Derivative-enhanced Deep Operator NetworkCode0
Designing Illuminant Spectral Power Distributions for Surface ClassificationCode0
Spatial Transcriptomics Dimensionality Reduction using Wavelet BasesCode0
A Systematic Performance Analysis of Deep Perceptual Loss Networks: Breaking Transfer Learning ConventionsCode0
Interactive Latent Interpolation on MNIST DatasetCode0
Principal Orthogonal Latent Components Analysis (POLCA Net)Code0
Spherical Rotation Dimension Reduction with Geometric Loss FunctionsCode0
Detecting covariate drift in text data using document embeddings and dimensionality reductionCode0
BERT4CTR: An Efficient Framework to Combine Pre-trained Language Model with Non-textual Features for CTR Prediction0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy90.9Unverified
2tSNEClassification Accuracy51.5Unverified
3IVISClassification Accuracy46.6Unverified
4UMAPClassification Accuracy41.3Unverified
#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy71.1Unverified
2QSClassification Accuracy68Unverified