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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 426–450 of 3304 papers

TitleStatusHype
A Theoretical Analysis of Noisy Sparse Subspace Clustering on Dimensionality-Reduced Data—0
A theoretical contribution to the fast implementation of null linear discriminant analysis method using random matrix multiplication with scatter matrices—0
A topological classifier to characterize brain states: When shape matters more than variance—0
A Topological "Reading" Lesson: Classification of MNIST using TDA—0
A Trace Lasso Regularized L1-norm Graph Cut for Highly Correlated Noisy Hyperspectral Image—0
A t-SNE Based Classification Approach to Compositional Microbiome Data—0
Attention-based Supply-Demand Prediction for Autonomous Vehicles—0
Approximation Algorithms for Sparse Principal Component Analysis—0
Attention or memory? Neurointerpretable agents in space and time—0
A Tutorial on Distance Metric Learning: Mathematical Foundations, Algorithms, Experimental Analysis, Prospects and Challenges (with Appendices on Mathematical Background and Detailed Algorithms Explanation)—0
A Hybrid Deep Learning CNN Model for Enhanced COVID-19 Detection from Computed Tomography (CT) Scan Images—0
A Two-Stage Dual-Path Framework for Text Tampering Detection and Recognition—0
A Two-Stage Federated Learning Approach for Industrial Prognostics Using Large-Scale High-Dimensional Signals—0
Approximate Matrix Multiplication with Application to Linear Embeddings—0
Audio Visual Speech Recognition using Deep Recurrent Neural Networks—0
Approximate Grassmannian Intersections: Subspace-Valued Subspace Learning—0
Augment on Manifold: Mixup Regularization with UMAP—0
A Unified Framework for Optimization-Based Graph Coarsening—0
A Hybrid Data-Driven Approach For Analyzing And Predicting Inpatient Length Of Stay In Health Centre—0
A Unifying Family of Data-Adaptive Partitioning Algorithms—0
Auto-adaptative Laplacian Pyramids for High-dimensional Data Analysis—0
Auto-Detection of Safety Issues in Baby Products—0
A Deep Embedded Refined Clustering Approach for Breast Cancer Distinction based on DNA Methylation—0
Autoencoder Enhanced Realised GARCH on Volatility Forecasting—0
Active Linear Regression for _p Norms and Beyond—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