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Methods/Spectral Clustering

Spectral Clustering

GeneralIntroduced 2000518 papers

Description

Spectral clustering has attracted increasing attention due to the promising ability in dealing with nonlinearly separable datasets [15], [16]. In spectral clustering, the spectrum of the graph Laplacian is used to reveal the cluster structure. The spectral clustering algorithm mainly consists of two steps: 1) constructs the low dimensional embedded representation of the data based on the eigenvectors of the graph Laplacian, 2) applies k-means on the constructed low dimensional data to obtain the clustering result. Thus,

Papers Using This Method

Data-Driven Soil Organic Carbon Sampling: Integrating Spectral Clustering with Conditioned Latin Hypercube Optimization2025-06-12 Accelerating Spectral Clustering under Fairness Constraints2025-06-09 Adaptive Per-Tree Canopy Volume Estimation Using Mobile LiDAR in Structured and Unstructured Orchards2025-06-09 Strongly Consistent Community Detection in Popularity Adjusted Block Models2025-06-08 Identifying Alzheimer's Disease Prediction Strategies of Convolutional Neural Network Classifiers using R2* Maps and Spectral Clustering2025-06-04 Near-Optimal Clustering in Mixture of Markov Chains2025-06-02 Enhancing Drug Discovery: Autoencoder-Based Latent Space Augmentation for Improved Molecular Solubility Prediction using LatMixSol2025-05-30 Spectral clustering for dependent community Hawkes process models of temporal networks2025-05-28 On the Geometry of Semantics in Next-token Prediction2025-05-13 On the Price of Differential Privacy for Spectral Clustering over Stochastic Block Models2025-05-09 A Method for Handling Negative Similarities in Explainable Graph Spectral Clustering of Text Documents -- Extended Version2025-04-16 Unsupervised Learning: Comparative Analysis of Clustering Techniques on High-Dimensional Data2025-03-29 Using Machine Learning for Lunar Mineralogy-I: Hyperspectral Imaging of Volcanic Samples2025-03-28 Neural Normalized Cut: A Differential and Generalizable Approach for Spectral Clustering2025-03-12 How Feasible is Augmenting Fake Nodes with Learnable Features as a Counter-strategy against Link Stealing Attacks?2025-03-12 Coreset Spectral Clustering2025-03-10 Multi-view Spectral Clustering on the Grassmannian Manifold With Hypergraph Representation2025-03-08 Minimax-Optimal Dimension-Reduced Clustering for High-Dimensional Nonspherical Mixtures2025-02-04 Generative Kernel Spectral Clustering2025-02-04 SiLVR: Scalable Lidar-Visual Radiance Field Reconstruction with Uncertainty Quantification2025-02-04