首页|Reports on Support Vector Machines from Guangdong University of Technology Provide New Insights (Privileged Multi-view One-class Support Vector Machine)
Reports on Support Vector Machines from Guangdong University of Technology Provide New Insights (Privileged Multi-view One-class Support Vector Machine)
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NETL
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Elsevier
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on Support Vector Machines have been published. According to news reporting originating from Guangzhou, People’s Republic of China, by NewsRx correspondents,research stated, “One -class support vector machine (OCSVM) is a typical one -class classification approach, which learns the classifier by using only the target samples. At present, most OCSVM works hypothesize that the samples have only one view, while multi -view OCSVM has not been taken into account.” Funders for this research include National Natural Science Foundation of China (NSFC), National Natural Science Foundation of Guangdong Province. Our news editors obtained a quote from the research from the Guangdong University of Technology, “In this paper, a novel multi -view one -class support vector machine method with privileged information learning (MOCPIL) is put forward. MOCPIL embodies both the consensus principle and complementarity principle in multi -view learning. Privileged information is additional data that is available only in the training process, but not in the testing process. By introducing the idea of privileged information learning, MOCPIL implements the complementarity principle by treating one view as the training data and the other view as the privileged data. Moreover, MOCPIL implements the consensus principle by requiring that different views of the same object should give similar predicting outputs. The learning problem of MOCPIL is a quadratic programming (QP) problem, which is able to be solved by off -the -shelf QP solvers. To the best of our knowledge, this is the first study to tackle the multi -view learning problem based on OCSVM. The performance of MOCPIL is evaluated through extensive experiments.”
GuangzhouPeople’s Republic of ChinaAsiaEmerging Tech- nologiesMachine LearningSupport Vector MachinesVector MachinesGuangdong University of Tech- nology
NETL
NSTL
Elsevier
