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个人简介
I worked primarily with Prof. Chris Wallace - see, e.g., "Foreword re C. S. Wallace", Computer Journal, Vol. 51, No. 5 (Sept. 2008) [Christopher Stewart WALLACE (1933-2004) memorial special issue], pp523-560 (and here).
Publications: most of my work and publications are in the theory and applications of the (information-theoretic) Minimum Message Length (MML) principle of statistical and inductive inference and machine learning (and econometrics and "knowledge discovery" and "data mining"), dating back to Wallace and Boulton (1968). MML and closely related methods (see also Minimum Description Length [MDL]) have much to say about the philosophy of science, philosophy of inference, the "Turing test", philosophy of mind and intelligence; and are useful in medicine and many other fields.
I was Program Chair of the Information, Statistics and Induction in Science (ISIS) conference, held in Melbourne, Australia on 20-23 August 1996; attended by R. J. Solomonoff (see also obituary: online and scanned), C. S. Wallace, J. J. Rissanen and others. (MML relates to the work of these people and Greg Chaitin, to the field variously known as Kolmogorov complexity or algorithmic information theory and to Claude Shannon (1916-2001)'s work on information theory - see. e.g., "Minimum Message Length and Kolmogorov complexity".)
I was an invited speaker at the iAstro Workshop and MC Meeting (Compliance and Conformity, Exception and Anomaly, in Science and Engineering), London, England, U.K., 8-9 July 2005.
Chris Wallace and I are authors of the Snob program for unsupervised clustering and mixture modelling, whose documentation you are invited to look at. Snob does Minimum Message Length (MML) mixture modelling of Gaussian, discrete multi-state (Bernoulli or categorical), Poisson and von Mises circular distributions. Further details on Snob are given here. The Snob software is available - subject to conditions - for private, academic use. One of many other areas I have published in includes using MML to make generalised Bayesian networks (or generalised MML Bayes nets, or generalised MML Bayesian nets, or generalised MML Bayesian networks) (or generalised directed graphical models, or generalised MML directed graphical models) with a mix of both continuous and discrete variables (Comley and Dowe, 2003) (Comley and Dowe, 2005).
(Please see my publications to find out other MML-related things that I get up to.)
I am seminar co-ordinator for the departmental Minimum Message Length (MML) Research group meetings.
Introductory material that I have written on MML includes Wallace and Dowe (1993), "MML estimation of the von Mises concentration parameter", TR #93/193, Dept of Comp Sci, Monash. Other material includes Wallace and Dowe (1999a), "Minimum Message Length and Kolmogorov complexity", Comp. J., Vol 42, No. 4, pp270-283 [which is the Computer Journal's most downloaded ``full text as .pdf'' article - see, e.g., here].
See also my Monash University CSSE Hons. course CSE455 Learning and Prediction II: MML Data Mining, on MML.
研究兴趣
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Hoai-An Nguyen,Anton Y. Peleg,Jiangning Song, Bhavna Antony,Geoffrey I. Webb,Jessica A. Wisniewski,Luke V. Blakeway,Gnei Z. Badoordeen,Ravali Theegala, Helen Zisis,David L. Dowe,Nenad Macesic
biorxiv(2023)
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Applied Data Analytics - Principles and Applicationspp.291-325, (2022)
2021 International Conference on Data Science, Artificial Intelligence, and Business Analytics (DATABIA)pp.160-163, (2021)
hawaii international conference on system sciencespp.1550-1559, (2021)
arXiv (Cornell University) (2021)
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semanticscholar(2021)
IOP conference seriesno. 1 (2019): 012022
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