重庆国家应用数学中心 学院邮箱 English
首页江南娱乐体育官网入口党建思政师资队伍学科建设人才培养科学研究学生工作招生就业合作交流人才招聘
  学术报告
 合作办学 
 学术交流 
快速通道
 
相关链接
 
重师主页 科研系统 图书馆
教务系统 书记院长邮箱 OA系统
学术报告
当前位置: 首页 >> 旧栏目 >> 合作交流 >> 学术交流 >> 学术报告 >> 正文
学术报告——江波教授(上海财经大学)
2023-10-26 09:10     (点击: )


报告名称:L_p-sphere covering and approximating nuclear p-norm

主讲人: 教授

邀请人:罗洪林 教授

时间:20231027 10 : 00

地点:江南娱乐体育官网入口X221学术报告厅

主办单位:江南娱乐体育官网入口


报告摘要

The spectral p-norm and nuclear p-norm of matrices and tensors appear in various applications albeit both are NP-hard to compute. The former sets a foundation of l_p-sphere constrained polynomial optimization problems and the latter has been found in many rank minimization problems in machine learning. We study approximation algorithms of the tensor nuclear p-norm with an aim to establish the approximation bound matching the best one of its dual norm, the tensor spectral p-norm. Driven by the application of sphere covering to approximate both tensor spectral and nuclear norms (p = 2), we propose several types of hitting sets that approximately represent `p-sphere with adjustable parameters for different levels of approximations and cardinalities, providing an independent toolbox for decision making on `p-spheres. Using the idea in robust optimization and second-order cone programming, we obtain the first polynomial-time algorithm with an O(1)-approximation bound for the computation of the matrix nuclear p-norm when p (2,) is a rational, paving a way for applications in optimization with the matrix nuclear p-norm. These two new results enable us to propose various polynomial-time approximation algorithms for the computation of the tensor nuclear p-norm using tensor partitions, convex optimization and duality theory, attaining the same approximation bound to the best one of the tensor spectral p-norm.

 

专家简介

江波,上海财经大学信息管理与工程学院常聘教授,副院长;国家级青年人才、上海市高校特聘教授(东方学者)、上海市青年拔尖人才。从事运筹优化、收益管理、机器学习等方向的研究。成果发表于运筹优化与机器学习的国际顶级期刊《Operations Research》、《Mathematics of Operations Research》、《Mathematical Programming》、《Journal of Machine Learning Research》。为顺丰、京东、太平金科、永辉等多个国内著名企业提供无人仓库内优化、智能定价、智能选址、智能排班等技术服务。获得了中国运筹学会青年科技奖、上海市自然科学奖二等奖等荣誉。

关闭窗口

重庆师范大学江南娱乐体育官网入口  地址:重庆市沙坪坝区大学城中路37号 汇贤楼
电话:023-65362798  邮编:401331