{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/adaptive-low-rank-kernel-subspace-clustering","title":"Adaptive Low-Rank Kernel Subspace Clustering","arxiv_id":"1707.04974","date":"2017-07-17","proceeding":null,"authors":["Pan Ji","Ian Reid","Ravi Garg","Hongdong Li","Mathieu Salzmann"],"abstract":"In this paper, we present a kernel subspace clustering method that can handle\nnon-linear models. In contrast to recent kernel subspace clustering methods\nwhich use predefined kernels, we propose to learn a low-rank kernel matrix,\nwith which mapped data in feature space are not only low-rank but also\nself-expressive. In this manner, the low-dimensional subspace structures of the\n(implicitly) mapped data are retained and manifested in the high-dimensional\nfeature space. We evaluate the proposed method extensively on both motion\nsegmentation and image clustering benchmarks, and obtain superior results,\noutperforming the kernel subspace clustering method that uses standard\nkernels[Patel 2014] and other state-of-the-art linear subspace clustering\nmethods.","url_abs":"http://arxiv.org/abs/1707.04974v4","url_pdf":"http://arxiv.org/pdf/1707.04974v4.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"adaptive-low-rank-kernel-subspace-clustering","repo_url":"https://github.com/panji1990/Low-rank-kernel-subspace-clustering","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"clustering","task_name":"Clustering"},{"task_slug":"image-clustering","task_name":"Image Clustering"},{"task_slug":"motion-segmentation","task_name":"Motion Segmentation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}