报告题目：A biased stochastic conjugate gradient algorithm in machine learning

报告人：袁功林 教授/博导，广西大学

报告时间：2025年5月16日（周五）上午9:00-10:00

报告地点：数理楼306会议室

主办单位：999策略手机论坛版

报告对象：微数学院全体师生，全校其他感兴趣的老师和学生

报告摘要：Conjugate gradient (CG) algorithms are widely applied to machine learning problems owing to their low calculation cost compared with second-order methods and better convergence properties relative to gradient descent methods. This study proposes a biased stochastic conjugate gradient (BSCG) algorithm with an adaptive step size. Specifically, the BSCG algorithm integrates both the stochastic recursive gradient method (SARAH) and the modified Barzilai-Borwein (BB) technique into the typical stochastic gradient algorithm. Compared with most of the available stochastic gradient methods, which obtain step size by selecting a fixed size elaborately and may lead to unfeasibility in finding an optimal solution, the proposed algorithm uses second-order information to gain an appropriate step size without increasing the computational cost. We not only prove that the proposed algorithm converges to global optimum, but also builds up its linear convergence rate for nonconvex objective functions. The numerical results of two machine learning models demonstrate show the superiority of the BSCG algorithm.

报告人简介：袁功林，广西大学数学与信息科学学院教授，博导，副院长，广西应用数学中心（广西大学）常务副主任，国家一流专业负责人；主要从事优化理论与方法及其应用方面研究，主持国家基金、广西杰出青年基金、广西重点基金、中央主导地方科技发展基金、广西科技基地和人才专项基金等项目；宝钢教育奖，广西十百千第二层次人选，广西特聘青年专家，广西卓越学者计划人选，南宁市高层次人才；以第一或通讯作者发表SCI论文60余篇，成果发表在SIAM J. Optim.，COAP，JOTA，JOGO，Expert Systems With Applications，Statistics and Computing等期刊，其中0.1%论文2篇、1%论文6篇、专著2部；入选2024全球2%顶尖科学家榜单，获得广西自然科学二等奖2项；任中国数学会理事、中国运筹学会理事、中国运筹学会数学规划分会理事、中国运筹学会算法软件与应用分会理事、广西数学会常务理事、广西运筹学会副理事长。