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对等网络中的级联的方法

Cascade RSVM in Peer-to-Peer Networks
课程网址: http://videolectures.net/ecmlpkdd08_gopalkrishnan_crip/  
主讲教师: Wee Keong Ng; Hock Hee Ang; Vivekanand Gopalkrishnan; Steven C. H. Hoi
开课单位: 南洋理工大学
开课时间: 信息不详。欢迎您在右侧留言补充。
课程语种: 英语
中文简介:
P2P网络中分布式学习的目标是尽可能接近集中学习的结果。P2P网络中的分类学习模型面临着可扩展性、对等动态性、异步性和数据隐私保护等挑战。本文研究了在P2P网络中建立支持向量机分类器的可行性。我们展示了如何将级联支持向量机映射到数据传输的P2P网络。我们提出的P2P支持向量机为P2P网络中分类器的构造提供了一种方法,其分类精度与集中式分类器相当,且优于其他分布式分类器。该算法也满足了P2P计算的特点,并且具有较高的通信开销上限。大量的实验结果证实了该方法的可行性和吸引力。
课程简介: The goal of distributed learning in P2P networks is to achieve results as close as possible to those from centralized approaches. Learning models of classification in a P2P network faces several challenges like scalability, peer dynamism, asynchronism and data privacy preservation. In this paper, we study the feasibility of building SVM classifiers in a P2P network. We show how cascading SVM can be mapped to a P2P network of data propagation. Our proposed P2P SVM provides a method for constructing classifiers in P2P networks with classification accuracy comparable to centralized classifiers and better than other distributed classifiers. The proposed algorithm also satisfies the characteristics of P2P computing and has an upper bound on the communication overhead. Extensive experimental results confirm the feasibility and attractiveness of this approach.
关 键 词: 支持向量机; 计算机科学; P2P
课程来源: 视频讲座网
最后编审: 2020-05-23:杨雨(课程编辑志愿者)
阅读次数: 26