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Michael Irwin Jordan (born 1956) is an American scientist, Professor at the University of California, Berkeley and leading researcher in machine learning and artificial intelligence.〔David M. Blei, Andrew Y. Ng, Michael I. Jordan. Latent Dirichlet allocation. The Journal of Machine Learning Research, Volume 3, 3/1/2003〕〔Michael I. Jordan, ed. Learning in Graphical Models. Proceedings of the NATO Advanced Study Institute, Ettore Maiorana Centre, Erice, Italy, September 27-October 7, 1996〕 == Biography == Jordan was born in Ponchatoula, Louisiana,〔(Bayesian or Frequentist, Which are You? ) Machine Learning Summer School (MLSS), Cambridge 2009〕 to a working-class family, and received his BS magna cum laude in Psychology in 1978 from the Louisiana State University, his MS in Mathematics in 1980 from the Arizona State University and his PhD in Cognitive Science in 1985 from the University of California, San Diego.〔(Vitae MICHAEL I. JORDAN ) Department of Electrical Engineering and Computer Science, Department of Statistics, University of California. Accessed September 3, 2013〕 At the University of California, San Diego Jordan was a student of David Rumelhart and a member of the PDP Group in the 1980s. Jordan is currently a full professor at the University of California, Berkeley where his appointment is split across the Department of Statistics and the Department of EECS. He was a professor at MIT from 1988-1998.〔(Vitae MICHAEL I. JORDAN )〕 Jordan received numerous awards, including a best student paper award (with X. Nguyen and M. Wainwright) at the International Conference on Machine Learning (ICML 2004), a best paper award (with R. Jacobs) at the American Control Conference (ACC 1991), the ACM - AAAI Allen Newell Award, the IEEE Neural Networks Pioneer Award, and an NSF Presidential Young Investigator Award. In 2010 he was named a Fellow of the Association for Computing Machinery "for contributions to the theory and application of machine learning." It is notable that many of Jordan's graduate students and postdocs continue to strongly influence the machine learning field after their PhDs. Francis Bach, Zoubin Ghahramani, Tommi Jaakkola, Andrew Ng, Lawrence Saul and David Blei (all former students or postdocs of Jordan) have all continued to make significant contributions to the field. 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Michael I. Jordan」の詳細全文を読む スポンサード リンク
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