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Subspace Guided Collaborative Clustering Based on Optimal Transport

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Proceedings of the 12th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2020) (SoCPaR 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1383))

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Abstract

Collaborative clustering is a promising approach in the learning from other learners research area. Although extensive research have been done to improve the collaborative approaches, they still suffer from several issues, including the mechanism of exchanging the information and how to measure the quality of this information. In this paper we introduce a new model of collaboration guided by feature selection, where the main idea is to choose the features that give the best representation for each collaborator and guarantee the communication between them, while preserving the privacy of each collaborator. Collaborative clustering will be developed within the framework of the theory of optimal transport. Indeed, this theory offers a formalism that is highly adapted to collaboration between members of a set of collaborators. Extensive experiments were conducted on multiple data-sets to evaluate the proposed approach and demonstrate its utility.

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Author information

Authors and Affiliations

  1. LIPN UMR 7030 CNRS, Université Sorbonne Paris Nord, Villetaneuse, France

    Fatima-Ezzahraa Ben-Bouazza, Younès Bennani & Guénaël Cabanes

  2. LaMSN, La Maison des Sciences Numériques, Saint Denis, France

    Fatima-Ezzahraa Ben-Bouazza, Younès Bennani & Guénaël Cabanes

  3. LAMA-FSDM, Université Sidi Mohamed Ben Abdellah, Fes, Morocco

    Fatima-Ezzahraa Ben-Bouazza & Abdelfettah Touzani

Authors
  1. Fatima-Ezzahraa Ben-Bouazza
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  2. Younès Bennani
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  3. Abdelfettah Touzani
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  4. Guénaël Cabanes
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Corresponding author

Correspondence to Fatima-Ezzahraa Ben-Bouazza .

Editor information

Editors and Affiliations

  1. Scientific Network for Innovation and Research Excellence, Machine Intelligence Research Labs (MIR Labs), Auburn, WA, USA

    Ajith Abraham

  2. Systems Innovation, School of Engineering, The University of Tokyo, Bunkyo-ku, Tokyo, Japan

    Yukio Ohsawa

  3. Scientific Network for Innovation and Research Excellence, Machine Intelligence Research Labs (MIR Labs), Auburn, WA, USA

    Niketa Gandhi

  4. Vardhaman College of Engineering, Hyderabad, Telangana, India

    M.A. Jabbar

  5. Faculty of Sciences and Techniques, Hassan 1st University, Settat, Morocco

    Abdelkrim Haqiq

  6. Queen’s University, Belfast, UK

    Seán McLoone

  7. Northumbria University, Newcastle, UK

    Biju Issac

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Ben-Bouazza, FE., Bennani, Y., Touzani, A., Cabanes, G. (2021). Subspace Guided Collaborative Clustering Based on Optimal Transport. In: Abraham, A., et al. Proceedings of the 12th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2020). SoCPaR 2020. Advances in Intelligent Systems and Computing, vol 1383. Springer, Cham. https://doi.org/10.1007/978-3-030-73689-7_12

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