报告人：叶颀 教授（华南师范大学）

时间：2021年1月7日（星期四）下午3：30-4：30

地点：腾讯会议

会议ID：282 221 315

会议密码：010203

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.

联系人：郭正初（guozhengchu@zju.edu.cn）