Clustering

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Overview

Clustering seeks useful groupings when labels are absent or incomplete, helping reveal structure in data such as text, images, graphs, time series, and scientific measurements. Methods include centroid-based k-means, density and hierarchical clustering, graph and spectral methods, mixture models, and newer approaches that learn embeddings or use optimal transport; fairness, privacy, streaming, and federated settings add further constraints. Work also studies how to choose the number of clusters and assess stability, uncertainty, interpretability, and statistical significance. No single method works best across data types: deep methods do not consistently beat strong conventional algorithms, and reliable validation remains a central challenge.

Latest papers

CardsList

345 papers31 papers in the last four weeks, up 11% on the four weeks before. 0.2% of all new papers.

  1. Drawing Lines in Psychological Space: What K-means Clustering Reveals in Simulated and Real Psychometric Data

    May 7, 2026Pedro Henrique Ramos Pinto, Maria Jullyanna Ferreira Marques, Luiz Carlos Serramo LopezClustering

    Postgraduate Program in Cognitive and Behavioral Neuroscience (PPGNeC) - Federal University of Paraíba (UFPB) - João Pessoa, PB - Brazil · Center for Health Sciences (CCS) - Federal University of Paraíba (UFPB) - João Pessoa, PB - Brazil

  2. Gaussian mixture models in Hilbert spaces via kernel methods

    May 7, 2026Daniel López-Montero, Antonio Álvarez-López, Marcos MatabuenaKernel Mean EmbeddingsFunctional Data Analysis

    Friedrich-Alexander-Universität Erlangen-Nürnberg · Universidad Autónoma de Madrid · Mohamed bin Zayed University of Artificial Intelligence

  3. Jointly Learning Structured Representations and Stabilized Affinity for Human Motion Segmentation

    May 7, 2026Xianghan Meng, Zhiyuan Huang, Zhengyu Tong +1Representation LearningClustering

    School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing 100876, P.R. China

  4. Scalable inference of spatial regions and temporal signatures from time series

    May 6, 2026Jiayu Weng, Alec KirkleyClusteringTime Series Clustering

    Institute of Data Science, University of Hong Kong, Hong Kong SAR, China · School of Computing and Data Science, University of Hong Kong, Hong Kong SAR, China · Department of Urban Planning and Design, University of Hong Kong, Hong Kong SAR, China +1

  5. Gradient Flow Structure and Quantitative Dynamics of Multi-Head Self-Attention

    May 5, 2026Ayan PendharkarSoftmax AttentionAttention Head Analysis

  6. AdaGraph: A Graph-Native Clustering Algorithm That Overcomes the Curse of Dimensionality and Enables Scientific Discovery

    May 5, 2026Ahmed ElmahdiClusteringGraph Clustering

    Independent Researcher

  7. Towards Robust and Scalable Density-based Clustering via Graph Propagation

    May 1, 2026Yingtao Zheng, Hugo Phibbs, Ninh PhamGraph-Based Label PropagationClustering

    School of Computer Science, University of Auckland, New Zealand. · Department of Mathematics and Computer Science, University of Southern Denmark, Denmark.

  8. Efficient Multivector Retrieval with Token-Aware Clustering and Hierarchical Indexing

    Apr 30, 2026Silvio Martinico, Franco Maria Nardini, Cosimo Rulli +1ClusteringVector Quantization

    University of Pisa & ISTI–CNR · Pisa, Italy · ISTI–CNR +1

  9. ClimateVID -- Social Media Videos Analysis and Challenges Involved

    Apr 30, 2026Shiqi Xu, Moritz Burmester, Katharina Prasse +3VLM EvaluationSocial Media Analysis

    University of Mannheim · Technical University of Munich · University of Mannheim, Max-Planck-Institute for Informatics, Saarland Informatics Campus

  10. Physically-Informed Fuzzy Clustering of Vertical Sounding Ionograms

    Apr 30, 2026Oleg I. Berngardt, Sergey N. PonomarchukClusteringRemote Sensing

  11. Characterizing Admissible Objective Functions for Hierarchical Clustering

    Apr 26, 2026Ryuki Tsukuba, Kazutoshi AndoClusteringHierarchical Clustering

    Graduate School of Integrated Science and Technology, Shizuoka University,Jun Hamamatsu, Shizuoka 432-8561, Japan · Faculty of Engineering, Shizuoka University, Johoku 3-5-1, 432-8561 Hamamatsu, Japan

  12. Explainable AI in Speaker Recognition -- Making Latent Representations Understandable

    Apr 25, 2026Yanze Xu, Wenwu Wang, Mark D. PlumbleyClusteringHierarchical Clustering

    Centre for Vision, Speech and Signal Processing, University of Surrey, Guildford, GU2 7XH, UK · Department of Informatics, King’s College London, London, WC2R 2LS, UK

  13. Turtle shell clustering: A mixture approach to discriminative clustering with applications to flow cytometry and other data

    Apr 25, 2026Mackenzie R. Neal, Paul D. McNicholas, Arthur WhiteClusteringGaussian Mixture Models

    Department of Mathematics & Statistics, McMaster University, Ontario, Canada · School of Computer Science & Statistics, Trinity College Dublin, Ireland

  14. Associativity-Peakiness Metric for Contingency Tables

    Apr 24, 2026Naomi E. Zirkind, William J. DiehlClustering

    Army Research Directorate, DEVCOM Army Research Laboratory, 2800 Powder Mill Road, Adelphi, 20783, MD, USA.

  15. How Hard Is Continuous Clustering? Lower Bounds from the Existential Theory of the Reals

    Apr 24, 2026Angshul MajumdarClusteringDensity-Based Clustering

    IIIT Delhi

  16. Robust Fuzzy local k-plane clustering with mixture distance of hinge loss and L1 norm

    Apr 24, 2026Junjun Huang, Xiliang Lu, Xuelin Xie +1Clustering

    China Electric Power Research Institute, Wuhan 430074, China, and also with the Key Laboratory of Measurement and Test of High Voltage and Heavy Current, State Administration for Market Regulation, Wuhan 430074, China · School of Mathematics and Statistics, Wuhan University, Wuhan 430072, China, the National Center for Applied Mathematics in Hubei, Wuhan University, Wuhan 430072, China, and also with the Hubei Key Laboratory of Computational Science, Wuhan University, Wuhan 430072, China · National Center for Applied Mathematics in Hubei, Wuhan University, Wuhan 430072, China, the Wuhan Institute for Math and AI, Wuhan University, Wuhan 430072, China, the School of Mathematics and Statistics, Wuhan University, Wuhan 430072, China, and the Hubei Key Laboratory of Computational Science, Wuhan University, Wuhan 430072, China

  17. Assessing the impact of dimensionality reduction on clustering performance - a systematic study

    Apr 23, 2026Ousmane Assani Amate, Elyes Lounissi, Mohammadreza Bakhtyari +3Principal Component AnalysisClustering

    Université du Québec à Montréal, Montreal, Quebec, Canada · Mila - Quebec AI Institute, Montreal, Quebec, Canada

  18. An effective variant of the Hartigan kk-means algorithm

    Apr 23, 2026François Clément, Stefan SteinerbergerClusteringUnsupervised Clustering

  19. FB-NLL: A Feature-Based Approach to Tackle Noisy Labels in Personalized Federated Learning

    Apr 21, 2026Abdulmoneam Ali, Ahmed ArafaClusteringNoisy-Label Learning

    Department of Electrical and Computer Engineering, University of North Carolina at Charlotte, NC 28223, USA

  20. Deep Sprite-based Image Models: An Analysis

    Apr 21, 2026Zeynep Sonat Baltacı, Romain Loiseau, Mathieu AubryClusteringObject-Centric Representation Learning

    LIGM, CNRS, Univ Gustave Eiffel, ENPC, Institut Polytechnique de Paris, France

  21. An Adaptive Spatiotemporal Clustering Framework for 3D Ocean Subsurface Temperature Reconstruction

    Apr 21, 2026Ming Shan Loo, Wengen Li, Xudong Jiang +4Clustering

    School of Computer Science and Technology, Tongji University, Shanghai, China · The Key Laboratory of Road and Traffic Engineering, Ministry of Education, College of Transportation, Tongji University, Shanghai, China · Project Management Office of China National Scientific Seafloor Observatory, Tongji University, Shanghai, China

  22. Preserving Clusters in Error-Bounded Lossy Compression of Particle Data

    Apr 20, 2026Congrong Ren, Sheng Di, Katrin Heitmann +2Clustering

    The Ohio State University · Argonne National Laboratory

  23. Clusterability-Based Assessment of Potentially Noisy Views for Multi-View Clustering

    Apr 20, 2026Mudi Jiang, Jiahui Zhou, Xinying Liu +2ClusteringMulti-View Learning

    School of Software, Dalian University of Technology, Dalian, China · School of Software, Dalian University of Technology, Dalian, China, and Key Laboratory for Ubiquitous Network and Service Software of Liaoning Province, Dalian, China

  24. Constant-Factor Approximations for Doubly Constrained Fair k-Center, k-Median and k-Means

    Apr 17, 2026Nicole Funk, Annika Hennes, Johanna Hillebrand +1ClusteringGroup Fairness

    Department of Informatics, University of Cologne, Germany · Heinrich Heine University Düsseldorf, Faculty of Mathematics and Natural Sciences, Germany · Department of Informatics, University of Bonn, Germany

  25. Why Colors Make Clustering Harder:Global Integrality Gaps, the Price of Fairness, and Color-Coupled Algorithms in Chromatic Correlation Clustering

    Apr 17, 2026Ibne Farabi Shihab, Sanjeda Akter, Anuj SharmaClusteringApproximation Algorithms

    Department of Computer Science, Iowa State University · Department of Civil, Construction & Environmental Engineering, Iowa State University

  26. Scalable Model-Based Clustering with Sequential Monte Carlo

    Apr 16, 2026Connie Trojan, Pavel Myshkov, Paul Fearnhead +3Clustering

    Lancaster University · Microsoft Research

  27. Composite Silhouette: A Subsampling-based Aggregation Strategy

    Apr 15, 2026Aggelos Semoglou, Aristidis Likas, John PavlopoulosCluster Number EstimationClustering

    Athens University of Economics and Business, Greece. · Archimedes, Athena Research Center, Greece. · University of Ioannina, Greece.

  28. Deep Spatially-Regularized and Superpixel-Based Diffusion Learning for Unsupervised Hyperspectral Image Clustering

    Apr 14, 2026Vutichart Buranasiri, James M. MurphySuperpixel SegmentationClustering

    Department of Mathematics, Tufts University, Medford, MA 02155, USA

  29. Enhancing Clustering: An Explainable Approach via Filtered Patterns

    Apr 14, 2026Motaz Ben Hassine, Saïd JabbourClusteringUnsupervised Clustering

    CRIL · CRIL, University of Artois & CNRS, Lens, France

  30. Leveraging Weighted Syntactic and Semantic Context Assessment Summary (wSSAS) Towards Text Categorization Using LLMs

    Apr 13, 2026Shreeya Verma Kathuria, Nitin Mayande, Sharookh Daruwalla +2Text ClusteringText Classification

    Tellagence Inc. · Villanova School of Business, Villanova University