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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 1551–1575 of 3304 papers

TitleStatusHype
SKFAC:Training Neural Networks with Faster Kronecker-Factored Approximate CurvatureCode1
Wireless Federated Learning with Limited Communication and Differential Privacy—0
WiCluster: Passive Indoor 2D/3D Positioning using WiFi without Precise LabelsCode1
Visualizing Representations of Adversarially Perturbed InputsCode0
Smaller Is Better: An Analysis of Instance Quantity/Quality Trade-off in Rehearsal-based Continual Learning—0
An Impossibility Theorem for Node Embedding—0
Hierarchical Subspace Learning for Dimensionality Reduction to Improve Classification Accuracy in Large Data Sets—0
Investigating Manifold Neighborhood size for Nonlinear Analysis of LIBS Amino Acid Spectra—0
Estimating leverage scores via rank revealing methods and randomizationCode1
Distribution Agnostic Symbolic Representations for Time Series Dimensionality Reduction and Online Anomaly DetectionCode0
DumbleDR: Predicting User Preferences of Dimensionality Reduction Projection Quality—0
A Clustering Framework for Residential Electric Demand ProfilesCode0
Theoretical Foundations of t-SNE for Visualizing High-Dimensional Clustered Data—0
Brain Inspired Face Recognition: A Computational Framework—0
A hyperparameter-tuning approach to automated inverse planningCode1
Forensic Analysis of Video Files Using Metadata—0
Covariance Matrix Adaptation Evolution Strategy Assisted by Principal Component Analysis—0
Enhancing ensemble learning and transfer learning in multimodal data analysis by adaptive dimensionality reduction—0
Empirical Evaluation of Pre-trained Transformers for Human-Level NLP: The Role of Sample Size and DimensionalityCode0
High-dimensional Functional Graphical Model Structure Learning via Neighborhood Selection ApproachCode0
Contextual Bandits with Sparse Data in Web setting—0
Ovarian Cancer Detection based on Dimensionality Reduction Techniques and Genetic Algorithm—0
Pseudocell Tracer—A method for inferring dynamic trajectories using scRNAseq and its application to B cells undergoing immunoglobulin class switch recombinationCode0
Automatic Collection Creation and Recommendation—0
Stochastic Mutual Information Gradient Estimation for Dimensionality Reduction NetworksCode0
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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