Yinyu Ye (Stanford University)

Time:

• 11:00-12:00 (Time in Beijing)
• March 25, 2023 (Monday)

Venue:

518, Research Building 4

Abstract:

The Fisher and Arrow-Debreu markets are the most fundamental models for resource/good allocation and exchange. However, classical markets (i) only consider two types of constraints, i.e., budgets of individual buyers and capacities of goods, and (ii) involve a complete information setting wherein buyers’ utilities are known, and all the transactions happen in a static market. In this talk, we present generalizations of classical market equilibrium price designs to settings when agents arrive at the market sequentially with utilities and budgets/goods that are not known a priori to the market designer. More specifically, we assume that agents arrive sequentially at the market with utility and budget parameters drawn i.i.d. from some distribution and make online or exchanges in real-time. In this setting, we study the performance limitations of static pricing approaches, which set the same prices for all agents; and develop two adaptive pricing algorithms, one with knowledge of the distribution and another that solely relies on past observations of user consumption, i.e., revealed preference feedback, with provable performance guarantees.

Speaker Bio:

Yinyu Ye is currently the K.T. Li Professor of Engineering at Department of Management Science and Engineering and Institute of Computational and Mathematical Engineering, Stanford University. His current research topics include Continuous and Discrete Optimization, Data Science and Applications, Numerical Algorithm Design and Analyses, Algorithmic Game/Market Equilibrium。 Operations Research and Management Science etc.; and he was one of the pioneers ofInterior-Point Methods, Conic Linear Programming, Distributionally Robust Optimization, Online Linear Programming and Learning, Algorithm Analyses for Reinforcement Learning and Markov Decision Process, and etc. He has received several scientific awards including, including the 2009 John von Neumann Theory Prize for fundamental sustained contributions to theory in Operations Research and the Management Sciences, the inaugural 2012 ISMP Tseng Lectureship Prize for outstanding contribution to continuous optimization (every three years), the 2014 SIAM Optimization Prize awarded (every three years), etc.. According to Google Scholar, his publications have been cited 58,000 times.

叶荫宇 (Yinyu Ye) 现任斯坦福大学管理科学与工程系及计算数学工程研究院李国鼎讲座教授。他的主要研究方向为连续和离散优化, 数据科学及应用， 数字算法设计及分析， 算法博弈及市场均衡，运筹及管理科学等；他和其他科学家开创了内点优化算法，锥规划模型，分布式鲁棒优化，在线线性规划和学习，强化学习和马可夫过程算法分析等。他多次获得科学奖项: 包括2009约翰·冯·洛伊曼理论奖，国际数学规划2012 Tseng Lectureship Prize（每三年），2014美国应用数学学会优化奖（每三年）等。根据谷歌学术统计，目前他的文章被引用总计超过58,000次。