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Phase transition of random plaquette models
Tiling with Electrons: fractionalization and emergent symmetry
Pyroptosis & Innate Immunity: Mechanisms & Therapeutics Potentials
【数学之美-杰出学者讲坛】2024年第6期 || Some recent results on conformally in...
报告题目:
自动化系海外访问学者面对面交流——马尔科夫影响网络分析
 报告人:
Bernd Heidergott
Bernd Heidergott(阿姆斯特丹自由大学)
报告时间:
2016-06-08 14:00
报告地点:
FIT 1-312
主办单位:
清华大学自动化系智能与网络化系统研究中心(CFINS)
  简介:
与Bernd Heidergott教授面对面交流
6月8日下午主题:
The Measure-valued Differentiation Approach to Gradient Estimation
摘要:Measure-valued differentation (MVD) is next to IPA and the Score
Fuction method one of the three main techniques for estatblishing unbiased
gradient estimators. We give a gentle introduction into MVD and illustrate
its relation with IPA and the Score Function.
主讲人简介:Bernd Heidergott is Chair of Stochastic Optimization at the Department of Econometrics and Operations Research at the Faculty of Economics and Business Administration of the Vrije Universiteit Amsterdam. At this university he is program director of the bachelor and master program Econometrics and Operations Research, and member of the board of the Amsterdam Business Research Institute (ABRI). Before joining the VU University Amsterdam he held post-doc positions at Erasmus University Rotterdam, Eindhoven University of Technology, Delft University of Technology, and EURANDOM. He is author of two monographs and more than 40 international journal papers. Bernd Heidergott is ABRI Research Fellow, and Tinbergen Institute Fellow.
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