报告题目：A stochastic Nesterov’s smoothing accelerated method for general nonsmooth constrained stochastic composite convex optimization
报告人：张超 教授（北京交通大学）
报告时间：2022年4月25日（周一）上午10:00 -11:30
报告地点：腾讯会议 会议ID：846-312-915
校内报告联系人：刘永朝 教授 联系电话：84708351-8141
报告摘要：
We propose a novel stochastic Nesterov’s smoothing accelerated method for general nonsmooth, constrained, stochastic composite convex optimization, the nonsmooth component of which may be not easy to compute its proximal operator. The proposed method combines Nesterov’s smoothing accelerated method for deterministic problems and stochastic approximation for stochastic problems, which allows three variants: single sample and two different mini-batch sizes per iteration, respectively. We prove that all the three variants achieve the best-known complexity bounds in terms of stochastic oracle. Numerical results on a support vector machine problem show that the proposed method compares favorably with other state-of-the-art first-order methods, and the variants with mini-batch sizes outperform the variant with single sample.
报告人简介： 张超，北京交通大学数学与统计学院教授、博士生导师。2008年日本弘前大学博士毕业，导师陈小君教授。主要从事随机优化、非光滑优化的理论和算法研究，取得多项国际领先成果。在领域顶尖期刊SIAM J. Optim.，Math. Programming, SIAM J. Sci. Comput., IEEE trans. Image Process., IEEE trans. Neural Network, Transportation Res. Part B. 发表科研论文8篇。主持召开1次国际学术会议。完成国家自然科学基金青年基金1项，国家自然科学基金面上项目1项，目前正在主持国家自然科学基金面上项目1项；主持北京市自然科学基金面上项目1项。
