IEEE CIS Webinar: Bilevel Optimization Recent Advancements on Methods and Applications скачать в хорошем качестве

IEEE CIS Webinar: Bilevel Optimization Recent Advancements on Methods and Applications

The talk will present a comprehensive review of techniques proposed in the literature for solving bilevel optimization problems encountered in various real-life applications. Bilevel optimization is an appropriate choice for hierarchical decision-making situations, where a decision-maker needs to consider a possible response from another decision-maker for each of her actions to achieve her own goals. Mathematically, it leads to a nested optimization structure, in which the primary decision-maker's optimization problem contains the secondary decision-maker’s optimization problem as a constraint. Various forms of bilevel problems, including linear, mixed-integer, single-objective, and multi-objective, will be discussed with focus on both classical and evolutionary approaches. Along with an overview of various areas of applications, two recent considerations of bilevel approach will be highlighted. The first application involves a bilevel decomposition approach for solving general optimization problems. A large-scale dataset with the potential to automating optimization will also be introduced. The second application addresses Neural Architecture Search (NAS), which is a prime example of a bilevel optimization problem in the area of machine learning, with architecture parameters optimized at the upper level while network weights optimized at the lower level. This talk will present a structured overview of NAS through the lens of bilevel optimization. Speaker Biography: Ankur Sinha is a professor at Indian Institute of Management Ahmedabad (IIMA), the Chairperson of the 2-year MBA program and the Chairperson of the Brij Disa Centre for Data Science and Artificial Intelligence. He completed his PhD from Helsinki School of Economics (Now: Aalto University School of Business) in the area of Business Technology, where his PhD thesis was adjudged as the best dissertation of the year 2011. He holds a Bachelor’s degree in Mechanical Engineering from Indian Institute of Technology Kanpur (IITK). After completing his PhD, he has held visiting professor positions at Michigan State University and Aalto University. His research interests include Bilevel Optimization, Neural Architecture Search and Decision Making. He has published his research in some of the leading Business, Computer Science and Statistics journals. Along with teaching and research, he is actively involved in mentoring startups, and consulting private and government organizations.