mlsanityData to 14 Oct 2026

Deep k-Means: Jointly clustering with k-Means and learning representations

arXiv 1806.10069 ↗First posted 26 Jun 2018cs.LG stat.MLcited by 50

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Abstract (arXiv)

We study in this paper the problem of jointly clustering and learning representations. As several previous studies have shown, learning representations that are both faithful to the data to be clustered and adapted to the clustering algorithm can lead to better clustering performance, all the more so that the two tasks are performed jointly. We propose here such an approach for k-Means clustering based on a continuous reparametrization of the objective function that leads to a truly joint solution. The behavior of our approach is illustrated on various datasets showing its efficacy in learning representations for objects while clustering them.

Key facts. Cited by 50 papers in the map (data through 14 Oct 2026). First posted on arXiv 26 Jun 2018.

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Citing papers per year: 2021: 9; 2022: 8; 2023: 8; 2024: 12; 2025: 4; 2026: 9.

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  1. 2023Effective Neural Topic Modeling with Embedding Clustering Regularizationcited by 46
  2. 2022Orchestra: Unsupervised Federated Learning via Globally Consistent Clusteringcited by 45
  3. 2024FASTopic: Pretrained Transformer is a Fast, Adaptive, Stable, and Transferable Topic Modelcited by 35
  4. 2021Pseudo-supervised Deep Subspace Clusteringcited by 29
  5. 2024Beyond Concept Bottleneck Models: How to Make Black Boxes Intervenable?cited by 28
  6. 2021Unsupervised Selective Labeling for More Effective Semi-Supervised Learningcited by 27
  7. 2021Quantization and Deployment of Deep Neural Networks on Microcontrollerscited by 21
  8. 2021Towards Clustering-friendly Representations: Subspace Clustering via Graph Filteringcited by 14
  9. 2021Deep Embedded K-Means Clusteringcited by 12
  10. 2023Deep Clustering of Tabular Data by Weighted Gaussian Distribution Learningcited by 12
  11. 2023Rethinking Image Forgery Detection via Soft Contrastive Learning and Unsupervised Clusteringcited by 12
  12. 2021Adaptive Attribute and Structure Subspace Clustering Networkcited by 9
38 more
  1. 2024A Rapid Review of Clustering Algorithmscited by 9
  2. 2022Effectiveness of Deep Image Embedding Clustering Methods on Tabular Datacited by 7
  3. 2022TUSK: Task-Agnostic Unsupervised Keypointscited by 5
  4. 2022K-textures, a self-supervised hard clustering deep learning algorithm for satellite image segmentationcited by 4
  5. 2023Adaptive Graph Convolutional Subspace Clusteringcited by 4
  6. 2024Dying Clusters Is All You Need -- Deep Clustering With an Unknown Number of Clusterscited by 4
  7. 2023Convolutional Autoencoders, Clustering and POD for Low-dimensional Parametrization of Navier-Stokes Equationscited by 3
  8. 2023Enhancing Interpretable Object Abstraction via Clustering-based Slot Initializationcited by 3
  9. 2024Deep Clustering with Self-Supervision using Pairwise Similaritiescited by 3
  10. 2024Polytopic Autoencoders with Smooth Clustering for Reduced-order Modelling of Flowscited by 2
  11. 2026Differentiable Rule Induction from Raw Sequence Inputscited by 2
  12. 2026Mining Electronic Health Records to Investigate Effectiveness of Ensemble Deep Clusteringcited by 2
  13. 2022Deep clustering with fusion autoencodercited by 1
  14. 2022Variational Autoencoder with Disentanglement Priors for Low-Resource Task-Specific Natural Language Generationcited by 1
  15. 2022VAESim: A probabilistic approach for self-supervised prototype discoverycited by 1
  16. 2023Jacobian-Scaled K-means Clustering for Physics-Informed Segmentation of Reacting Flowscited by 1
  17. 2023Deep Structure and Attention Aware Subspace Clusteringcited by 1
  18. 2026DDCL: Deep Dual Competitive Learning: A Differentiable End-to-End Framework for Unsupervised Prototype-Based Representation Learningcited by 1
  19. 2021Instance segmentation with the number of clusters incorporated in embedding learningcited by 0
  20. 2021Separating Boundary Points via Structural Regularization for Very Compact Clusterscited by 0
  21. 2021Transformed K-means Clusteringcited by 0
  22. 2022Deep Multi-View Semi-Supervised Clustering with Sample Pairwise Constraintscited by 0
  23. 2024Unsupervised Optimisation of GNNs for Node Clusteringcited by 0
  24. 2024Imbalanced Data Clustering using Equilibrium K-Meanscited by 0
  25. 2024Deep polytopic autoencoders for low-dimensional linear parameter-varying approximations and nonlinear feedback designcited by 0
  26. 2024Sonic: Fast and Transferable Data Poisoning on Clustering Algorithmscited by 0
  27. 2024SHADE: Deep Density-based Clusteringcited by 0
  28. 2024An Approach Towards Learning K-means-friendly Deep Latent Representationcited by 0
  29. 2025Deep Clustering via Gradual Community Detectioncited by 0
  30. 2025CycleGuardian: A Framework for Automatic RespiratorySound classification Based on Improved Deep clustering and Contrastive Learningcited by 0
  31. 2025Random Normed k-Means: A Paradigm-Shift in Clustering within Probabilistic Metric Spacescited by 0
  32. 2025Classification EM-PCA for clustering and embeddingcited by 0
  33. 2026Accelerated Full Waveform Inversion by Deep Compressed Learningcited by 0
  34. 2026NPCNet: Navigator-Driven Pseudo Text for Deep Clustering of Early Sepsis Phenotypingcited by 0
  35. 2026Khatri-Rao Clustering for Data Summarizationcited by 0
  36. 2026Visual Perceptual to Conceptual First-Order Rule Learning Networkscited by 0
  37. 2026Converge to Surprise: Evolutionary Self-supervised Image Clusteringcited by 0
  38. 2026Ensemble of Unsupervised Deep Learning for Clustering Imbalanced Tabular Datacited by 0