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

347 papers33 papers in the last four weeks, up 18% on the four weeks before. 0.2% of all new papers.

  1. Cluster-Aware Matching via Laplacian Optimal Transport

    Jul 17, 2026Gabriel Samberg, YoonHaeng Hur, Yuehaw Khoo +1ClusteringGraph Matching

    Department of Applied Mathematics, Tel Aviv University · Department of Statistics, Columbia University · Department of Statistics, University of Chicago

  2. Data-Native Global Optimization for Big Data K-means Clustering

    Jul 17, 2026Ravil Mussabayev, Rustam Mussabayev, Zukhra Yerdaliyeva +1ClusteringUnsupervised Clustering

    AI Research Lab, Satbayev University, Almaty, 050000, Kazakhstan · Laboratory for Analysis and Modeling of Information Processes, Institute of Information and Computational Technologies, Almaty, 050010, Kazakhstan

  3. Measuring Spatial Clustering via Metropolis-Hastings Diffusion Distance

    Jul 16, 2026Thomas Weighill, Chidinma WilliamsClusteringGraph Diffusion

    Department of Mathematics and Statistics, University of North Carolina at Greensboro, Greensboro, NC 27402

  4. Counterfactuals for Feature-Weighted Clustering

    Jul 16, 2026Richard J. Fawley, Renato Cordeiro de AmorimCounterfactual ExplanationsClustering

    School of Computer Science and Electronic Engineering, University of Essex, Wivenhoe, UK.

  5. Deployable Human Preference Alignment in Robotics: Learning Representative Rewards from Diverse Human Preferences

    Jul 14, 2026Taehyung Kim, Gwangmo Lee, Minjun Chang +2ClusteringPreference Alignment

    Yonsei University, Seoul, South Korea · Georgia Institute of Technology, United States of America · Hyundai Motor Company, Seoul, South Korea

  6. Cluster-Weighted EDMD

    Jul 14, 2026Lorenzo Tomaz, Judd Rosenblatt, Flavio Kicis +2Koopman Operator LearningLatent Dynamics Modeling

    AE Studio

  7. Beyond Looking Up, Try Looking Around: Harmonizing Global Structure and Local Consistency in Optimal Transport for Short Text Clustering

    Jul 12, 2026Zhihao Yao, Yuxuan Gu, Jixuan Yin +1ClusteringUnsupervised Clustering

    Harbin Engineering University, China · Harbin Institute of Technology, China

  8. Graph Representation of RaagBase: A Unique Dataset for Hindustani Music

    Jul 11, 2026Chandan Misra, Swarup ChattopadhyayClusteringMusic Information Retrieval

  9. Performance Benchmarking and Optimisation of Clustering Algorithms for Local and Non-Local Similarity Measure in Medical Image Analysis

    Jul 10, 2026Sisipho Hamlomo, Marcellin AtemkengMedical Image AnalysisClustering

    Department of Mathematics, Rhodes University, PO Box 94, Makhanda, 6140, South Africa · Department of Statistics, Rhodes University, PO Box 94, Makhanda, 6140, South Africa · National Institute for Theoretical and Computational Sciences (NITheCS), Stellenbosch 7600, South Africa

  10. An interpretable Good--Turing restart criterion for k-means++

    Jul 9, 2026Renato Cordeiro de AmorimEarly StoppingClustering

    School of Computer Science and Electronic Engineering, University of Essex, Colchester, UK.

  11. Equivariant Quantum Clustering with Differential Privacy: Parameter-Efficient Privacy-Preserving Analysis Across Heterogeneous Sensitive Datasets

    Jul 9, 2026B. M. Taslimul Haq, Md Arifur Rahman, Tawfiq Al Islam Foysal +2ClusteringQuantum Machine Learning

    Department of Information Systems, Central Michigan University, Mount Pleasant, MI, USA. · Department of Computer and Information Sciences, Trine University, Angola, IN, USA. · Department of Computer Science and Engineering, American International University–Bangladesh (AIUB), Dhaka, Bangladesh. +2

  12. FMMVCC: Fuzzy Mamba-based Multi-View Contrastive Clustering for Univariate Time Series

    Jul 8, 2026Donato Cerciello, Leonardo Schiavo, Angel Panizo-LLedot +2Self-Supervised Time Series Representation LearningClustering

    Departamento de Sistemas Inform´aticos, Universidad Polit´ecnica de Madrid Madrid, Spain

  13. Converge to Surprise: Evolutionary Self-supervised Image Clustering

    Jul 8, 2026Canlin Zhang, Xiuwen LiuUnsupervised LearningSelf-Supervised Learning

    Independent Researcher · Department of Computer Science Florida State University

  14. Sensitivity Sampling with Predictions for k-Means Clustering

    Jul 6, 2026Cristian Boldrin, Fabio VandinClusteringImportance Sampling

    University of Padova, Padova, Italy

  15. Framework for Grouping Local Process Models

    Jul 6, 2026Viki Peeva, Wil M. P. van der AalstProcess MiningClustering

    Chair of Process and Data Science (PADS), RWTH Aachen University, Ahronstrasse 55, Aachen, 52074, North Rhine-Westphalia, Germany.

  16. Learnable Weighting of Intra-Attribute Distances for Categorical Data Clustering with Nominal and Ordinal Attributes

    Jul 6, 2026Yiqun Zhang, Yiu-ming CheungClusteringMetric Learning

  17. Scalable and Distributed Silhouette Approximation

    Jul 2, 2026Ilie Sarpe, Federico Altieri, Andrea Pietracaprina +2Clustering

    KTH Royal Institute of Technology · University of Padova

  18. Statistical Properties of kk-means Clustering for Data Missing Completely at Random

    Jul 2, 2026Xin GuanClusteringUnsupervised Clustering

    Graduate School of Information Sciences Tohoku University Sendai, Miyagi 980-8579, Japan

  19. UT-AISTimprt submission for ICME 2026 Grand Challenge on Academic Text-to-Music Generation

    Jul 2, 2026Shunsuke Yoshida, Yu-Hua Chen, Satoru FukayamaText-to-Music GenerationClustering

    University of Tokyo, Japan · National Institute of Advanced Industrial Science and Technology (AIST), Japan

  20. GSRQ: Gain-Shape Residual Quantization for Sub-1-bit KV Cache

    Jul 1, 2026Soosung Kim, Minjae Park, Eui-Young Chung +1LLM CompressionResidual VQ

    Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea · Department of Systems Semiconductor Engineering, Yonsei University, Seoul, Republic of Korea

  21. MNAR-kk-means: A kk-means Clustering for Data Missing Not at Random with Magnitude-Decaying Probability

    Jun 30, 2026Xin GuanClusteringLearning with Missing Data

    Graduate School of Information Sciences Tohoku University Sendai, Miyagi 980-8579, Japan

  22. Consensus Clustering of Free-Viewing Gaze Data: New Insights into Human-Information Interaction

    Jun 29, 2026Beryl Gnanaraj, Jaya Sreevalsan-Nair, Saqib Alam Ansari +1Ensemble LearningClustering

    Graphics-Visualization-Computing Lab, International Institute of Information Technology Bangalore, Karnataka 560100, India. · 2PSG College of Technology, Coimbatore, Tamin Nadu, India.

  23. Nonlinear mixture model motivated subspace clustering

    Jun 28, 2026Ivica KoprivaClustering

    Division of Computing and Data Science, Ruđer Bošković Instute, Zagreb, Croatia

  24. scKDGM: KAN-guided Dynamic Graph Masked Learning for Single-Cell RNA-seq Clustering

    Jun 26, 2026Jun Tang, Pengwei Hu, Sicong Gao +3Graph SSLClustering

    College of Computer and Information Science, Southwest University, Chongqing, China · Xinjiang Technical Institute of Physics and Chemistry, Chinese Academy of Sciences, Urumqi, China

  25. How to evaluate clustering with ground truth?

    Jun 25, 2026Pasi FräntiClustering

    School of Computing University of Eastern Finland Joensuu, Finland

  26. Term-Centric Hierarchy Induction from Heterogeneous Corpora

    Jun 25, 2026Elena Senger, Yuri Campbell, Jan-Peter Bergmann +2ClusteringHierarchical Clustering

    1MaiNLP, Center for Information and Language Processing, LMU Munich, Germany · 2Fraunhofer Institute for Systems and Innovation Research ISI, Germany · Department of Computer Science, IT University of Copenhagen, Denmark

  27. Universal Guideline-Driven Image Clustering via a Hybrid LLM Agent

    Jun 23, 2026Wenliang Zhong, Rob Barton, Lucas Goncalves +7ClusteringUnsupervised Clustering

    1The University of Texas at Arlington · 2Amazon

  28. Fursee: Hybrid YOLO-DINOv3 Framework for Fursuit Identity Retrieval and Clustering

    Jun 22, 2026Jundi WuVision Foundation ModelsImage Matching

    Shandong University Qingdao, China

  29. Noise is Signal: Density-Based Outliers as Leading Indicators of Occupational Emergence in Labor Market Text

    Jun 22, 2026Shreyash RawatClusteringComputational Social Science

    Independent Researcher · Redmond, WA, USA

  30. Cohort Organized Learning: Clustering Through Agreement

    Jun 19, 2026Finn Henry O'Shea, Maria Elena MonzaniUnsupervised LearningClustering

    SLAC National Accelerator Laboratory, 2575 Sand Hill Road, Menlo Park, CA 94025-7015, USA · Kavli Institute for Particle Astrophysics and Cosmology, Stanford University, Stanford, CA 94305-4085 USA