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发表时间:2021-01-07 阅读次数:381次
报告题目: Solving Nonconvex Support Vector Machines by Alternating Direction Multiplier Methods
报 告 人:叶颀 教授
报告人所在单位:华南师范大学数学科学学院
报告日期:2021-01-07 星期四
报告时间:15:30-16:30
报告地点:腾讯会议ID: 282221315, 密码: 010203
  
报告摘要:
In this talk, we first present the generalized representer theorem in Banach spaces for generalized data. Based on the generalized representer theorem, we solve the nonconvex support vector machines in reproducing kernel Hilbert spaces by alternating direction multiplier methods. Next, we use the Kurdyka-Lojasiewicz inequality to prove the global convergence of the iterative solutions given by the nonconvex loss functions. Finally, we show the numerical examples of the simulated data and the real data.
  
本年度学院报告总序号:11

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