Tianyuan Mathematical Center
in Southwest China

Consensus-based High Dimensional Global Non-convex Optimization in Machine Learning

报告人：金石教授 上海交通大学

报告时间：8月4日16点—17点

报告地点：腾讯会议87141591553 无密码

摘要：We introduce a stochastic interacting particle consensus system for global optimization of high dimensional non-convex functions. This algorithm does not use gradient of the function thus is suitable for non-smooth functions. We prove that under dimensionindependent conditions on the parameters and initial data the algorithms converge to the neighborhood of the global minimum almost surely.