时 间：2015年11月23日(星期一)下午14:30
地 点：数理学院基础楼二楼报告厅
报 告 人：邹斌
题目：Support Vector Machine Classification Based on Markov Sampling
报告摘要：The previously known works studying the generalization ability of Support Vector Machine (SVM) classification algorithm are usually based on the assumption of independent and identically distributed (i.i.d.) samples. In this talk, we go far beyond this classical framework by studying the generalization ability of SVM classification (SVMC) based on uniformly ergodic Markov chain (u.e.M.c.) samples.
报告人简介：邹斌，湖北大学数学与统计学院教授。研究方向为统计学习理论、机器学习等。他主持多项国家自然科学基金面上项目、湖北省自然科学基金重点项目。在《IEEE Transactions on Neural Networks and Learning Systems》、《IEEE Transactions on Cybernetics》、《Neural Networks》、《Machine Learning》、《Science in China: Information Science》等国际期刊著名期刊上发表学术论文。
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