报 告 人:张莉 苏州大学计算机学院教授
报告题目:A fast approximation algorithm for 1-norm SVM with squared loss
报告地点:静远楼0908室
主办单位:计算机学院、科技处
报告内容简介: 1-norm support vector machine (SVM) has attracted substantial attentions for its good sparsity. However, the computational complexity of training 1-norm SVM is about the cube of the sample number, which is high. This paper replaces the hinge loss or the ε-insensitive loss by the squared loss in the 1-norm SVM, and applies orthogonal matching pursuit (OMP) to approximate the solution of the 1-norm SVM with the squared loss. Experimental results on toy and real-world datasets show that OMP can faster train 1-norm SVM and achieve similar learning performance compared with some methods available.
张莉教授个人简介:
张莉,女,博士,教授,博士生导师,江苏省杰出青年基金获得者,IEEE会员,中国计算机学会高级会员,中国电子学会会员。分别于1997年和2002年在西安电子科技大学获得工学学士和博士学位,博士论文被评选为陕西省优秀博士学位论文。2003年4月至2005年5月,在上海交通大学控制科学与工程博士后流动站工作。担任《IEEE Transactions on Pattern Recognition and Machine Intelligence 》,《IEEE Transactions on Neural Networks》、《Arabian Journal for Science and Engineering》,《模式识别与人工智能》等学术期刊及国际学术会议的审稿人。获教育部高等学校科学研究优秀成果自然科学一等奖和西安市科技进步一等奖;作为项目负责人,申请到两项国家自然科学基金、1项省自然科学基金。主要从事机器学习、模式识别、图像处理方面的研究工作。