Simplifying Poisson Processes for Non-parametric Methods
A lot of the major results for use of Poisson process models (the gamma, beta and Dirichlet processes, for instance) were done by Lancelot James in a series of papers 2009, 2010 and another just now 2016. The theory has not really filtered into the Machine Learning community, although the community makes great use of the models, for instance recent work in non-parametric Poisson-gamma matrix factorisation. In this talk, I'll review some of the major results: present a simplifying view of the Indian buffet process and its close relatives, for instance showing the correspondence between Poisson-gamma process modelling and multinomial-Dirichlet process modelling. I will also present recent results on hierarchical process modelling and explain what the hierarchical Pitman-Yor process really is.
About the speaker
Prof. Wray Buntine joined Monash University in February 2014 after 7 years at NICTA in Canberra Australia. At Monash he was founding director of the (online) Graduate Diploma of Data Science and is currently director of the Master of Data Science, the Faculty of IT's newest and in-demand degree, and he also heads up the Machine Learning Flagship research area in the faculty. He was previously at Helsinki Institute for Information Technology from 2002, and at NASA Ames Research Center, University of California, Berkeley, and Google. He is known for his theoretical and applied work in document and text analysis, data mining and machine learning, and probabilistic methods. He applies probabilistic and non-parametric methods to tasks such as text analysis. In 2009 he was programme co-chair of ECML-PKDD in Bled, Slovenia, and was programme co-chair of ACML in Singapore in 2012 and programme chair in Canberra in 2013. He reviews for conferences such as ACML, ECIR, SIGIR, ECML-PKDD, ICML, NIPS, UAI, and KDD, and is on the editorial board of Data Mining and Knowledge Discovery. He aso distributes C code for non-parametric topic models via MLOSS.
|LARC is supported by the National Research Foundation, Prime Minister's Office, Singapore under its International Research Centres in Singapore Funding Initiative.|
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