A tutorial on spectral clustering

2007/08/21 by Ulrike von Luxburg · 560 citations
Computer Science · Mathematics · Physics and Astronomy · #Advanced Graph Neural Networks #Complex Network Analysis Techniques #Graph theory and applications

paper · doi:10.1007/s11222-007-9033-z

openalex publication_date 2007/08/21 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/30

Citations

• Towards a theoretical foundation for Laplacian-based manifold methods
• Model-Based Clustering, Discriminant Analysis, and Density Estimation
• Laplacian Eigenmaps for Dimensionality Reduction and Data Representation

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• Orthogonal Nonnegative Tucker Decomposition
• Learning Laplacian Matrix in Smooth Graph Signal Representations
• Temporal Human Action Segmentation via Dynamic Clustering
• Unsupervised Co-Learning on G-Manifolds Across Irreducible Representations
• A central limit theorem for scaled eigenvectors of random dot product graphs
• A novel semi-supervised multi-view clustering framework for screening Parkinson's disease
• The decomposition of the higher-order homology embedding constructed from the k-Laplacian
• Persistent Clustering and a Theorem of J. Kleinberg
• Free Energy Node Embedding via Generalized Skip-gram with Negative Sampling
• Improved Spectral Clustering for Multi-Objective Controlled Islanding of Power Grid
• Transforming Graph Representations for Statistical Relational Learning
• Minimal Sample Subspace Learning: Theory and Algorithms
• Threshold Optimization and Dynamic Adaptation of Distributed Optimal Power Flow in 5G Networks
• Sample Truncation Strategies for Outlier Removal in Geochemical Data: The MCD Robust Distance Approach Versus t-SNE Ensemble Clustering
• Community-preserving Graph Convolutions for Structural and Functional Joint Embedding of Brain Networks
• Improved spectral convergence rates for graph Laplacians on epsilon-graphs and k-NN graphs
• Adapting Stochastic Block Models to Power-Law Degree Distributions
• Limit theorems for out-of-sample extensions of the adjacency and Laplacian spectral embeddings
• Deep Continuous Clustering
• Probabilistically Sampled and Spectrally Clustered Plant Genotypes using Phenotypic Characteristics
• Data spectroscopy: Eigenspaces of convolution operators and clustering
• Cutoff for exact recovery of Gaussian mixture models
• A Generic Framework for Clustering Vehicle Motion Trajectories
• Social connectedness and movements among communities of giraffes vary by sex and age class
• Advancing Local Clustering on Graphs via Compressive Sensing: Semi-supervised and Unsupervised Methods
• When Slepian Meets Fiedler: Putting a Focus on the Graph Spectrum
• Decoupling of brain function from structure reveals regional behavioral specialization in humans
• Guided graph spectral embedding: Application to the C. elegans connectome
• Community-Aware Graph Signal Processing
• A Graph Signal Processing Perspective on Functional Brain Imaging
• Semantic Level of Detail for Knowledge Graphs: Discovering Abstraction Boundaries via Spectral Heat Diffusion
• Scoring relevancy of features based on combinatorial analysis of Lasso with application to lymphoma diagnosis
• Geometry-aware Active Learning of Spatiotemporal Dynamic Systems
• Label-independent hyperparameter-free self-supervised single-view deep subspace clustering
• Signals on graphs: Transforms and tomograms
• Compressive Spectral Clustering
• Spectral redemption in clustering sparse networks
• Hierarchical Sparse Circuit Extraction from Billion-Parameter Language Models through Scalable Attribution Graph Decomposition
• Nonparametric Unsupervised Classification
• DIHARD II is Still Hard: Experimental Results and Discussions from the DKU-LENOVO Team
• Community detection based on the “clumpiness” matrix in complex networks
• Hypothesis testing for eigenspaces of covariance matrix
• Improving Open-World Object Localization by Discovering Background
• Clustering of Diverse Multiplex Networks
• Diffusion map for clustering fMRI spatial maps extracted by independent component analysis
• Early Detection of Multidrug Resistance Using Multivariate Time Series Analysis and Interpretable Patient-Similarity Representations
• Collaborative Multi-Agent Reinforcement Learning for Automated Feature Transformation with Graph-Driven Path Optimization
• Mask-GVAE: Blind Denoising Graphs via Partition
• Spectral Clustering for Jet Physics
• Solution path clustering with adaptive concave penalty
• Comprehensive Privacy Analysis of Deep Learning: Passive and Active White-box Inference Attacks against Centralized and Federated Learning
• Speaker Attribution with Voice Profiles by Graph-Based Semi-Supervised Learning
• Leveraging unsupervised image registration for discovery of landmark shape descriptor
• Inducing a hierarchy for multi-class classification problems
• Feature concatenation multi-view subspace clustering
• Recent advances in feature selection and its applications
• Active Orthogonal Matching Pursuit for Sparse Subspace Clustering
• Exploiting The Structure of Bipartite Graphs for Algebraic and Spectral Graph Theory Applications
• Comparative analysis on the selection of number of clusters in community detection
• Optimal Clustering in Anisotropic Gaussian Mixture Models
• Using networks and partial differential equations to forecast bitcoin price movement
• Cequel: Cost-Effective Querying of Large Language Models for Text Clustering
• Knowledge Network System (KNS) by Evolutionary Collective Intelligence (ECI): Model, Algorithm and Applications
• EigenGame Unloaded: When playing games is better than optimizing
• Stochastic Sparse Subspace Clustering
• Graph Topology Inference Based on Sparsifying Transform Learning
• Ensemble Kalman inversion: a derivative-free technique for machine learning tasks
• A model-based clustering algorithm with covariates adjustment and its application to lung cancer stratification
• How Local Separators Shape Community Structure in Large Networks
• Community detection in sparse time-evolving graphs with a dynamical Bethe-Hessian
• On a two-truths phenomenon in spectral graph clustering
• Analyzing Cause-Specific Mortality Trends using Compositional Functional Data Analysis
• Structural analysis based on unsupervised learning: Search for a characteristic low-dimensional space by local structures in atomistic simulations
• Statistics of Visual Responses to Image Object Stimuli from Primate AIT Neurons to DNN Neurons
• Minimum Class Confusion for Versatile Domain Adaptation
• Object tracking via non-Euclidean geometry: A Grassmann approach
• Geometric Formulation for Discrete Points and its Applications
• A Novel Efficient Approach with Data-Adaptive Capability for OMP-based Sparse Subspace Clustering
• Higher-Order Spectral Clustering for Geometric Graphs
• Transfer Regression via Pairwise Similarity Regularization
• Tools to Characterize the Correlated Nature of Collective Dynamics
• Spectral detection of simplicial communities via Hodge Laplacians
• Large Scale Spectral Clustering Using Resistance Distance and Spielman-Teng Solvers
• A Novel Framework Using Unsupervised Machine Learning for Aerosol Classification: A Case Study of North Indian AERONET Sites
• Scalable detection of statistically significant communities and hierarchies, using message passing for modularity
• A divisive spectral method for network community detection
• Inversion symmetry of singular values and a new orbital ordering method\n in tensor train approximations for quantum chemistry
• Deep divergence-based approach to clustering
• Stochastic Block Models are a Discrete Surface Tension
• Multiway Spectral Clustering: A Margin-Based Perspective
• A Scheme to Design Community Detection Algorithms in Various Networks
• Network Community Detection on Metric Space
• Weight thresholding on complex networks
• Revealing Social Networks of Spammers Through Spectral Clustering
• Multiway Spectral Clustering with Out-of-Sample Extensions through Weighted Kernel PCA
• On spectral partitioning of signed graphs
• A Method for Handling Negative Similarities in Explainable Graph Spectral Clustering of Text Documents -- Extended Version
• A Survey on Archetypal Analysis
• Fuzzy network jump models for soft dynamic clustering of graph-structured data
• Machine Learning at the Edge: A Data-Driven Architecture With Applications to 5G Cellular Networks
• Diffusion Operator Geometry of Feedforward Representations
• Re-imagining Spectral Graph Theory
• Correlative and Discriminative Label Grouping for Multi-Label Visual Prompt Tuning
• A geometric view of Biodiversity: scaling to metagenomics
• The Impact of External Sources on the Friedkin-Johnsen Model
• Dual Boost-Driven Graph-Level Clustering Network