{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T02:05:16Z","timestamp":1760148316946,"version":"build-2065373602"},"reference-count":43,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2023,4,19]],"date-time":"2023-04-19T00:00:00Z","timestamp":1681862400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Grants-in-Aid for Scientific Research (A)","award":["19H01095","20K11838","22J22908"],"award-info":[{"award-number":["19H01095","20K11838","22J22908"]}]},{"name":"Grants-in-Aid for Scientific Research (C)","award":["19H01095","20K11838","22J22908"],"award-info":[{"award-number":["19H01095","20K11838","22J22908"]}]},{"name":"Grants-in-Aid for JSPS Fellows","award":["19H01095","20K11838","22J22908"],"award-info":[{"award-number":["19H01095","20K11838","22J22908"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>Combinatorial clustering based on the Ising model is drawing attention as a high-quality clustering method.\u00a0However, conventional Ising-based clustering methods using the Euclidean distance cannot handle irregular data. To overcome this problem, this paper proposes an Ising-based kernel clustering method.\u00a0The kernel clustering method is designed based on two critical ideas.\u00a0One is to perform clustering of irregular data by mapping the data onto a high-dimensional feature space by using a kernel trick.\u00a0The other is the utilization of matrix\u2013matrix calculations in the numerical libraries to accelerate preprocess for annealing.\u00a0While the conventional Ising-based clustering is not designed to accept the transformed data by the kernel trick, this paper extends the availability of Ising-based clustering to process a distance matrix defined in high-dimensional data space. The proposed method can handle the Gram matrix determined by the kernel method as a high-dimensional distance matrix to handle irregular data.\u00a0By comparing the proposed Ising-based kernel clustering method with the conventional Euclidean distance-based combinatorial clustering, it is clarified that the quality of the clustering results of the proposed method for irregular data is significantly better than that of the conventional method. Furthermore, the preprocess for annealing by the proposed method using numerical libraries is by a factor of\u00a0up to\u00a012.4 million \u00d7 from the conventional naive python\u2019s implementation. Comparisons between Ising-based kernel clustering and kernel K-means reveal that the proposed method has the potential to obtain higher-quality clustering results than the kernel K-means as a representative of the state-of-the-art kernel clustering methods.<\/jats:p>","DOI":"10.3390\/a16040214","type":"journal-article","created":{"date-parts":[[2023,4,20]],"date-time":"2023-04-20T01:42:39Z","timestamp":1681954959000},"page":"214","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Ising-Based Kernel Clustering"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0903-064X","authenticated-orcid":false,"given":"Masahito","family":"Kumagai","sequence":"first","affiliation":[{"name":"Graduate School of Information Sciences, Tohoku University, 6-6-01 Aramaki Aza Aoba, Aoba-ku, Sendai 980-8579, Japan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4463-8359","authenticated-orcid":false,"given":"Kazuhiko","family":"Komatsu","sequence":"additional","affiliation":[{"name":"Cyberscience Center, Tohoku University, 6-3 Aramaki Aza Aoba, Aoba-ku, Sendai 980-8578, Japan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4186-5014","authenticated-orcid":false,"given":"Masayuki","family":"Sato","sequence":"additional","affiliation":[{"name":"Graduate School of Information Sciences, Tohoku University, 6-6-01 Aramaki Aza Aoba, Aoba-ku, Sendai 980-8579, Japan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3350-1413","authenticated-orcid":false,"given":"Hiroaki","family":"Kobayashi","sequence":"additional","affiliation":[{"name":"Graduate School of Information Sciences, Tohoku University, 6-6-01 Aramaki Aza Aoba, Aoba-ku, Sendai 980-8579, Japan"}]}],"member":"1968","published-online":{"date-parts":[[2023,4,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"5355","DOI":"10.1103\/PhysRevE.58.5355","article-title":"Quantum annealing in the transverse Ising model","volume":"58","author":"Kadowaki","year":"1998","journal-title":"Phys. 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