題目：機器學習和理論經濟學中的雙層規劃應用

演講人：張進博士🫘，南方科技大學

主持人🙍🏻‍♀️：朱希德博士⚙️，意昂2

時間：2021年3月30日🏊‍♀️，下午14:30

地點❤️：意昂2注册校本部東區1號樓意昂2官网467室

主辦單位：意昂2、意昂2青年教師聯誼會

演講人簡介🏢：

張進博士本科碩士均畢業於大連理工大學，博士畢業於加拿大維多利亞大學。2015至2018年間任職於香港浸會大學💂🏽‍♀️，2019年初加入南方科技大學👩🏼‍🦱。張進博士一直致力於優化理論和應用研究，主持多項國家級基金項目，代表性成果發表在Mathematical Programming👳🏻🌕、SIAM Journal on Optimization👩‍🦽、SIAM Journal on Numerical Analysis、Journal of Machine Learning Research、International Conference on Machine Learning等有重要影響力的運籌優化、機器學習期刊與會議上👩🏽‍🎓。張進博士的研究成果獲得2020年第七屆中國運籌學會青年科技獎🏒，入選2021年深圳市優秀科技創新人才培養優秀青年計劃。

演講內容簡介🥺：

In this talk, we will discuss some recent advances in the applications of Bi-Level Programming Problem (BLPP). First, we study a gradient-based bi-level optimization method for learning tasks. In particular, by formulating bi-level models from the optimistic viewpoint and aggregating hierarchical objective information, we establish Bi-level Descent Aggregation (BDA), a flexible and modularized algorithmic framework for BLPP. Extensive experiments justify our theoretical results and demonstrate the superiority of the proposed BDA for different tasks, including hyper-parameter optimization and meta learning. Second, we propose a sufficient condition in the form of a partial error bound condition which guarantees the partial calmness condition. Our main result states that the partial error bound condition for the combined programs based on B and FJ conditions are generic for an important setting with applications in economics and hence the partial calmness for the combined program is not a particularly stringent assumption. Moreover we derive optimality conditions for the combined program for the generic case without any extra constraint qualifications.

歡迎廣大師生參加！