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个人简介
I am an Applied Researcher at FUSE Labs UK. My main interest is applying machine learning and computational intelligence to real-world applications. I believe that computational intelligence can add great value to the next generation of online services. For example, personalization and filtering can open people's horizons by allowing them to discover useful content in the deluge of information being added to the web.
Previously I was a Post Doc Researcher at Microsoft Research Cambridge where I worked on large scale recommendation systems and computer Go.
I completed my PhD at David MacKay's Inference Group at the University of Cambridge. My thesis, 'Modelling Uncertainty in the Game of Go', presented a number of applications of machine learning to the game of Go. Go is an ancient Chinese game whose complexity has defeated attempts by Artificial Intelligence researchers to automate play. Typically in machine learning, uncertainty results from unpredictable aspects of the data which is often called 'noise'. In my work, I am primarily interested in uncertainty that results from a different source: limited computer speed (limited rationality). In Go, a board position in conjunction with the rules of the game contains all of the information necessary for perfect play. However, the sheer complexity of the game tree results in uncertainty about the future course of the game. I am interested in using probabilities (in the Bayesian sense) to represent and manage this uncertainty.
研究兴趣
论文共 22 篇作者统计合作学者相似作者
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mag(2012)
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Proceedings of the fourth ACM international conference on Web search and data mining - WSDM '11 (2011)
mag(2011)
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WSDMpp.465-474, (2011)
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