{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,22]],"date-time":"2026-01-22T00:22:51Z","timestamp":1769041371010,"version":"3.49.0"},"reference-count":25,"publisher":"World Scientific Pub Co Pte Lt","issue":"03n04","funder":[{"name":"National Science Foundation","award":["CCF-1422324"],"award-info":[{"award-number":["CCF-1422324"]}]},{"name":"National Science Foundation","award":["IIS-1422591"],"award-info":[{"award-number":["IIS-1422591"]}]},{"name":"National Science Foundation","award":["CCF-1716400"],"award-info":[{"award-number":["CCF-1716400"]}]},{"name":"National Science Foundation","award":["IIS-1910492"],"award-info":[{"award-number":["IIS-1910492"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Comput. Geom. Appl."],"published-print":{"date-parts":[[2020,9]]},"abstract":"<jats:p> In this paper, we consider the distributed version of Support Vector Machine (SVM) under the coordinator model, where all input data (i.e., points in [Formula: see text] space) of SVM are arbitrarily distributed among [Formula: see text] nodes in some network with a coordinator which can communicate with all nodes. We investigate two variants of this problem, with and without outliers. For distributed SVM without outliers, we prove a lower bound on the communication complexity and give a distributed [Formula: see text]-approximation algorithm to reach this lower bound, where [Formula: see text] is a user specified small constant. For distributed SVM with outliers, we present a [Formula: see text]-approximation algorithm to explicitly remove the influence of outliers. Our algorithm is based on a deterministic distributed top [Formula: see text] selection algorithm with communication complexity of [Formula: see text] in the coordinator model. <\/jats:p>","DOI":"10.1142\/s0218195920500107","type":"journal-article","created":{"date-parts":[[2021,7,18]],"date-time":"2021-07-18T05:28:15Z","timestamp":1626586095000},"page":"213-233","source":"Crossref","is-referenced-by-count":4,"title":["Distributed and Robust Support Vector Machine"],"prefix":"10.1142","volume":"30","author":[{"given":"Yangwei","family":"Liu","sequence":"first","affiliation":[{"name":"Department of Computer Science and Engineering, State University of New York at Buffalo, Buffalo, New York 14260-1660, United States"}]},{"given":"Hu","family":"Ding","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, University of Science and Technology of China, Hefei, Anhui, P. R. China"}]},{"given":"Ziyun","family":"Huang","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Software Engineering, Penn State Erie, the Behrend College, Erie, Pennsylvania 16563, United States"}]},{"given":"Jinhui","family":"Xu","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Engineering, State University of New York at Buffalo, Buffalo, New York 14260-1660, United States"}]}],"member":"219","published-online":{"date-parts":[[2021,7,16]]},"reference":[{"key":"S0218195920500107BIB001","doi-asserted-by":"publisher","DOI":"10.1007\/BF00994018"},{"key":"S0218195920500107BIB002","first-page":"2","volume":"1","author":"Luscombe N. 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