SOTAVerified

Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 826–850 of 3304 papers

TitleStatusHype
Scalable manifold learning by uniform landmark sampling and constrained locally linear embedding—0
Inference and Visualization of Community Structure in Attributed Hypergraphs Using Mixed-Membership Stochastic Block ModelsCode0
A Novel method for Schizophrenia classification using nonlinear features and neural networks—0
ANALYTiC: Understanding Decision Boundaries and Dimensionality Reduction in Machine Learning—0
Agnostically Learning Multi-index Models with Queries—0
Comparative Analysis of Radiomic Features and Gene Expression Profiles in Histopathology Data Using Graph Neural Networks—0
Efficient Estimation of the Central Mean Subspace via Smoothed Gradient Outer Products—0
Nowcasting Madagascar's real GDP using machine learning algorithms—0
Deep Learning for Efficient GWAS Feature Selection—0
Augment on Manifold: Mixup Regularization with UMAP—0
Convergence Visualizer of Decentralized Federated Distillation with Reduced Communication Costs—0
Language-Assisted 3D Scene Understanding—0
Unsupervised Learning for Fault Detection of HVAC Systems: An OPTICS -based Approach for Terminal Air Handling Units—0
A Powerful Face Preprocessing For Robust Kinship Verification based Tensor Analyses—0
Characterization of Phosphorylated Tau-Microtubule complex with Molecular Dynamics (MD) simulationCode0
Physics-Informed Representation and Learning: Control and Risk QuantificationCode0
Exploring UMAP in hybrid models of entropy-based and representativeness sampling for active learning in biomedical segmentation—0
Investigating Shallow and Deep Learning Techniques for Emotion Classification in Short Persian TextsCode0
A new method color MS-BSIF Features learning for the robust kinship verification—0
Data-Driven Socio-Economic Deprivation Prediction via Dimensionality Reduction: The Power of Diffusion MapsCode0
Automated detection of Zika and dengue in Aedes aegypti using neural spiking analysis—0
Featurizing Koopman Mode Decomposition For Robust ForecastingCode0
RdimKD: Generic Distillation Paradigm by Dimensionality Reduction—0
High-Dimensional Bayesian Optimisation with Large-Scale Constraints -- An Application to Aeroelastic Tailoring—0
Expand-and-Quantize: Unsupervised Semantic Segmentation Using High-Dimensional Space and Product Quantization—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