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Dimensionality Reduction

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

( Image credit: openTSNE )

Papers

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Showing 2026–2050 of 3304 papers

TitleStatusHype
Hyperspectral Image Analysis with Subspace Learning-based One-Class Classification—0
Hyperspectral Images Classification and Dimensionality Reduction using spectral interaction and SVM classifier—0
Hyperspectral images classification and Dimensionality Reduction using Homogeneity feature and mutual information—0
Hyperspectral Imaging and Analysis for Sparse Reconstruction and Recognition—0
Hyperspectral Remote Sensing Image Classification Based on Multi-scale Cross Graphic Convolution—0
Hypoelliptic Diffusion Maps I: Tangent Bundles—0
Quantum-Classical Hybrid Machine Learning for Image Classification (ICCAD Special Session Paper)—0
I-Con: A Unifying Framework for Representation Learning—0
ICU Patient Deterioration prediction: a Data-Mining Approach—0
Identifying Chemicals Through Dimensionality Reduction—0
Identifying Dominant Industrial Sectors in Market States of the S&P 500 Financial Data—0
Identifying Feedforward and Feedback Controllable Subspaces of Neural Population Dynamics—0
Identifying Layers Susceptible to Adversarial Attacks—0
Identifying manifolds underlying group motion in Vicsek agents—0
Identifying semantic relations in a specialized corpus through distributional analysis of a cooccurrence tensor—0
Identifying Shared Decodable Concepts in the Human Brain Using Image-Language Foundation Models—0
Identifying Transition States of Chemical Kinetic Systems using Network Embedding Techniques—0
"I know it when I see it". Visualization and Intuitive Interpretability—0
Image-Based Benchmarking and Visualization for Large-Scale Global Optimization—0
Image-based localization using LSTMs for structured feature correlation—0
Image Classification by Feature Dimension Reduction and Graph based Ranking—0
Image patch analysis and clustering of sunspots: a dimensionality reduction approach—0
Image retrieval method based on CNN and dimension reduction—0
Impact of Latent Space Dimension on IoT Botnet Detection Performance: VAE-Encoder Versus ViT-Encoder—0
Impact of the composition of feature extraction and class sampling in medicare fraud detection—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