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وبینار امور بین الملل: Wasserstein Distributionally Robust Optimization: Theory and Applications in Machine Learning

وبینار امور بین الملل: Wasserstein Distributionally Robust Optimization: Theory and Applications in Machine Learning

ارائه علمی با موضوع
Wasserstein Distributionally Robust Optimization: Theory and Applications in Machine Learning
با سخنرانی جناب آقای پروفسور Daniel Kuhn در دوم شهریور ماه 1400

وبینار امور بین الملل: Wasserstein Distributionally Robust Optimization: Theory and Applications in Machine Learning

Daniel Kuhn

Daniel Kuhn is Professor of Operations Research at the College of Management of Technology at EPFL, where he holds the Chair of Risk Analytics and Optimization (RAO). His research focuses on stochastic and robust optimization. Before joining EPFL, Daniel Kuhn was a faculty member in the Department of Computing at Imperial College London (2007-2013) and a postdoctoral research associate in the Department of Management Science and Engineering at Stanford University (2005-2006). He holds a PhD degree in Economics from University of St. Gallen and an MSc degree in Theoretical Physics from ETH Zurich. He serves as the area editor for continuous optimization for Operations Research and as an associate editor for several other journals including Management Science, Mathematical Programming, Mathematics of Operations Research and Operations Research Letters

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