{"id":501,"date":"2022-08-17T08:20:56","date_gmt":"2022-08-17T08:20:56","guid":{"rendered":"https:\/\/vinuni.edu.vn\/research\/?post_type=event&p=501"},"modified":"2022-09-19T03:58:19","modified_gmt":"2022-09-19T03:58:19","slug":"mathematical-optimization-for-machine-learning-and-decision","status":"publish","type":"event","link":"https:\/\/vinuni.edu.vn\/research\/event\/mathematical-optimization-for-machine-learning-and-decision\/","title":{"rendered":"Mathematical Optimization for Machine Learning and Decision"},"content":{"rendered":"
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Speaker:\u00a0<\/strong>YINYU YE<\/strong>,\u00a0<\/span>K.T. Li Professor of Engineering,\u00a0<\/span>Department of Management Science and Engineering and Institute\u00a0<\/span>for Computational and Mathematical Engineering, Stanford University<\/span><\/p>\n

Wednesday, August 17, 2022 | 4.30 \u2013 5.30 pm (Hanoi time)<\/b>
\nC202 | Zoom Meeting<\/b><\/strong><\/p>\n

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Abstract<\/strong>: We present a few recent mathematical optimization case studies driven by Machine Learning applications. We show how newly developed (convex) optimization models and numerical algorithms can be effectively used to achieve solution efficiency and near optimality in many fields. They include Wireless Ad-Hoc Sensor Network localization and tracking, Energy Management System and Optimal PEV Charging\/Discharging, Dynamic Unit-Commitment algorithms to balance demand and supply in large Power-Grids,\u00a0 an efficient Divide-and-Conquer algorithm for vehicle assignment and routing.<\/p>\n

Bio<\/strong>: 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. He received the B.S. degree in System Engineering from the Huazhong University of Science and Technology, China, and the M.S. and Ph.D. degrees in Engineering-Economic Systems and Operations Research from Stanford University. His current research interests include Continuous and Discrete Optimization, Data Science and Application, Algorithm Design and Analysis, Computational Game\/Market Equilibrium, Metric Distance Geometry, Dynamic Resource Allocation, and Stochastic and Robust Decision Making, etc. He is an INFORMS (The Institute for Operations Research and The Management Science) Fellow since 2012, and has received several academic awards including: the inaugural 2006 Farkas Prize on Optimization, the 2009 IBM Faculty Award, 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 winner of the 2014 SIAM Optimization Prize awarded (every three years), the 2015 SPS Signal Processing Magazine Best Paper Award, etc.. He has supervised numerous doctoral students at Stanford who received various prizes such as INFORMS Nicholson Prize, Student Paper Competition, the INFORMS Computing Society Prize, the INFORMS Optimization Prize for Young Researchers. According to Google Scholar, his publications have been cited 50,000 times.<\/p>\n

Lecture Record:<\/strong><\/p>\n<\/div>\n