A Framework for Deep Constrained Clustering
| Autor: | Sugato Basu, Ian Davidson, Hongjing Zhang, Tianyang Zhan |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
FOS: Computer and information sciences
Computer Science - Machine Learning Source code Computer Networks and Communications Computer science media_common.quotation_subject 02 engineering and technology Machine learning computer.software_genre Field (computer science) Machine Learning (cs.LG) Robustness (computer science) 020204 information systems 0202 electrical engineering electronic engineering information engineering media_common business.industry Deep learning Constrained clustering Mixture model Spectral clustering Computer Science Applications Domain knowledge 020201 artificial intelligence & image processing Artificial intelligence business computer Information Systems |
| Popis: | The area of constrained clustering has been extensively explored by researchers and used by practitioners. Constrained clustering formulations exist for popular algorithms such as k-means, mixture models, and spectral clustering but have several limitations. A fundamental strength of deep learning is its flexibility, and here we explore a deep learning framework for constrained clustering and in particular explore how it can extend the field of constrained clustering. We show that our framework can not only handle standard together/apart constraints (without the well documented negative effects reported earlier) generated from labeled side information but more complex constraints generated from new types of side information such as continuous values and high-level domain knowledge. Furthermore, we propose an efficient training paradigm that is generally applicable to these four types of constraints. We validate the effectiveness of our approach by empirical results on both image and text datasets. We also study the robustness of our framework when learning with noisy constraints and show how different components of our framework contribute to the final performance. Our source code is available at $\href{https://github.com/blueocean92/deep_constrained_clustering}{\text{URL}}$. Data Mining and Knowledge Discovery, 2021. arXiv admin note: substantial text overlap with arXiv:1901.10061 |
| Databáze: | OpenAIRE |
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