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理科

量子信息學(xué)交叉學(xué)科系列講座——Challenges and Opportunities of Quantum Machine Learning

發(fā)布時(shí)間:2020-11-23 瀏覽:次

報(bào)告人:Min-Hsiu Hsieh

時(shí)間:2020年11月27日 15:00

地點(diǎn):騰訊會(huì)議(會(huì)議號(hào):820281227)


Bio: Min-Hsiu Hsieh received his BS and MS in electrical engineering from National Taiwan University in 1999 and 2001, and PhD degree in electrical engineering from the University of Southern California, Los Angeles, in 2008. From 2008-2010, he was a Researcher at the ERATO-SORST Quantum Computation and Information Project, Japan Science and Technology Agency, Tokyo, Japan. From 2010-2012, he was a Postdoctoral Researcher at the Statistical Laboratory, the Centre for Mathematical Sciences, the University of Cambridge, UK. He is now an Australian Research Council (ARC) Future Fellow and an Associate Professor at the Centre for Quantum Software and Information, Faculty of Engineering and Information Technology, University of Technology Sydney, Australia. His scientific interests include quantum information, quantum learning, and quantum computation.

Abstract: In this talk, I will quickly review the current challenges faced in the research topic of quantum machine learning, and introduce some of our recent results that could go around and overcome these challenges.