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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 1851–1900 of 3304 papers

TitleStatusHype
Quantized Random Projections and Non-Linear Estimation of Cosine Similarity—0
Quantum artificial vision for defect detection in manufacturing—0
Quantum classification of the MNIST dataset with Slow Feature Analysis—0
Quantum Cognition Machine Learning for Forecasting Chromosomal Instability—0
Quantum diffusion map for nonlinear dimensionality reduction—0
Self-Adaptive Quantum Kernel Principal Components Analysis for Compact Readout of Chemiresistive Sensor Arrays—0
Quantum Laplacian Eigenmap—0
Quantum Machine Learning Applied to the Classification of Diabetes—0
Quick unsupervised hyperspectral dimensionality reduction for earth observation: a comparison—0
Quotient Based Multiresolution Image Fusion of Thermal and Visual Images Using Daubechies Wavelet Transform for Human Face Recognition—0
RAINER: A Robust Ensemble Learning Grid Search-Tuned Framework for Rainfall Patterns Prediction—0
Random Forest Autoencoders for Guided Representation Learning—0
Randomized Dimensionality Reduction for Facility Location and Single-Linkage Clustering—0
Randomized Dimensionality Reduction for Euclidean Maximization and Diversity Measures—0
Randomized Dimensionality Reduction for k-means Clustering—0
Randomized Dimension Reduction on Massive Data—0
Randomized Dimension Reduction with Statistical Guarantees—0
Randomized ICA and LDA Dimensionality Reduction Methods for Hyperspectral Image Classification—0
Randomized Iterative Algorithms for Fisher Discriminant Analysis—0
A Projector-Based Approach to Quantifying Total and Excess Uncertainties for Sketched Linear Regression—0
Randomized Principal Component Analysis for Hyperspectral Image Classification—0
Riemannian optimization with a preconditioning scheme on the generalized Stiefel manifold—0
Randomized Sketches of Convex Programs with Sharp Guarantees—0
Randomized Tensor Ring Decomposition and Its Application to Large-scale Data Reconstruction—0
Random Manhattan Integer Indexing: Incremental L1 Normed Vector Space Construction—0
Random matrix approach to estimation of high-dimensional factor models—0
Random Maxout Features—0
Random Positive-Only Projections: PPMI-Enabled Incremental Semantic Space Construction—0
Random Projection Estimation of Discrete-Choice Models with Large Choice Sets—0
Random Projections for Improved Adversarial Robustness—0
Random Projections for k-means Clustering—0
Random Projections for Linear Support Vector Machines—0
Random Projections for Manifold Learning—0
Random projections of random manifolds—0
Random Subspace Local Projections—0
Ranking Entities in the Age of Two Webs, an Application to Semantic Snippets—0
Rank Reduction Autoencoders—0
RdimKD: Generic Distillation Paradigm by Dimensionality Reduction—0
Rdimtools: An R package for Dimension Reduction and Intrinsic Dimension Estimation—0
Real time expert system for anomaly detection of aerators based on computer vision technology and existing surveillance cameras—0
Real-time Inflation Forecasting Using Non-linear Dimension Reduction Techniques—0
Real-time optimal control of high-dimensional parametrized systems by deep learning-based reduced order models—0
Real-time simulation of parameter-dependent fluid flows through deep learning-based reduced order models—0
Realtime Simulation of Thin-Shell Deformable Materials using CNN-Based Mesh Embedding—0
Real-time Wireless Transmitter Authorization: Adapting to Dynamic Authorized Sets with Information Retrieval—0
Reconstructing Big Semantic Similarity Networks—0
Recovery of Linear Components: Reduced Complexity Autoencoder Designs—0
Recurrent Neural Networks for Long and Short-Term Sequential Recommendation—0
Recurrent neural networks learn robust representations by dynamically balancing compression and expansion—0
Reduced Basis Decomposition: a Certified and Fast Lossy Data Compression Algorithm—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