 
Solomonoff 85th memorial 2011 : Solomonoff 85th memorial conference  
Link: http://www.Solomonoff85thMemorial.monash.edu.au  
 
Call For Papers  
Solomonoff 85th memorial conf', Nov/Dec 2011
RAY SOLOMONOFF (19262009) 85th MEMORIAL CONFERENCE  multidisciplinary 1st Call for Papers Melbourne, Australia Tues 29/Nov/2011  Fri 2/Dec/2011 Submission deadline: 20 May 2011 www.Solomonoff85thMemorial.monash.edu.au This is a multidisciplinary conference based on the wide range of applications of work related to or inspired by that of Ray Solomonoff. As well as ``artificial intelligence'', ``machine learning'', ``statistics'' and ``philosophy'', it is clear that the categories as keywords for this conference should also include (e.g.) ``mathematics'', ``linguistics'', ``AI'', ``computer science'', ``data mining'', ``bioinformatics'', ``computational intelligence'', ``computational science'', ``life sciences'', ``physics'', ``knowledge discovery'', ``ethics'', ``computational biology'', ``computational linguistics'', ``collective intelligence'', etc. Ray Solomonoff (19262009) was the originator (in 1964) of algorithmic information theory. Solomonoff's (1964) work preceded the slightly later independent work of Kolmogorov (1965) [from whom we have the term Kolmogorov complexity], shortly before the not unrelated work of the then teenage G. J. Chaitin (1966). But, unlike the slightly later Kolmogorov and Chaitin, Solomonoff (1964) also saw the relevance of this new area to statistics, machine learning, artificial intelligence and prediction  and coined the term algorithmic probability (ALP). Given a body of data, the algorithmic probability distribution behind Solomonoff prediction is obtained by doing a posteriorweighted averaging of the outputs of all available computable theories  with the prior probabilities of theories depending (monotonically decreasingly) upon the lengths of their encodings on the chosen Universal Turing Machine (UTM). Independently of and shortly after the above was the Minimum Message Length (MML) work of Wallace and Boulton (1968), based on very similar Bayesian informationtheoretic principles but instead focussing on the one single best model for statistical and inductive inference (and whose relationship with algorithmic information theory was formalised in the 1990s). The related Minimum Description Length (MDL) principle followed a decade later in Rissanen (1978), coincidentally taking the same form as Schwarz's (1978) Bayesian Information Criterion (BIC) of the same year  and with some approaches [such as the still popular but largely unrelated Akaike's Information Criterion (AIC)] formed after MML but before MDL. The (algorithmic) information theory behind both Solomonoff prediction and (the twopart form of) MML inference (or model selection and point estimation) leads to a variety of statistical consistency (or convergence) results  apparently more general than for other approaches  and likewise makes the results of both approaches statistically invariant to reparameterisation. These approaches  both the MML inductive or inferential approach to choosing the single ``best'' model and the Solomonoff predictive approach of weighting over the posterior to form a predictive distribution  are two of at least as many approaches from (Kolmogorov complexity or) algorithmic information theory which have been applied to a range of areas. Such areas include (e.g.) statistical inference (and model selection and point estimation) and prediction, machine learning, econometrics (including time series and panel data), in principle proofs of financial market inefficiency, knowledge discovery and ``data mining'', theories of (quantifying) intelligence and new forms of (universal) intelligence test (for robotic, terrestrial and extraterrestrial life), philosophy of science, the problem of induction, bioinformatics, linguistics, evolutionary (tree) models in biology and linguistics, geography, climate modelling and bushfire detection, environmental science, image processing, spectral analysis, engineering, arguments that entropy is not the arrow of time, etc. Of course, this list will continue to grow and is not exhaustive. Perhaps Solomonoff's next main contribution was the notion of ``infinity point'' (Solomonoff, 1985), later referred to as the ``singularity'', where machine intelligence catches up to and overtakes human intelligence  an increasingly discussed scenario which forms the basis of many science fiction films. Solomonoff's obituary from the New York Times (January 2010) is at www.nytimes.com/2010/01/10/science/10solomonoff.html , duplicated at www.csse.monash.edu.au/~dld/MML.html#rjs . In the year in which Ray Solomonoff would have had his 85th birthday and some weeks before the year in which Alan Turing (upon whose Universal Turing Machines much of Solomonoff's work is based) would have turned 100, this multidisclipinary conference is timed for late 2011. It also follows on 15 years after the Information, Statistics and Induction in Science (ISIS) conference in 1996 and also held in Melbourne, Australia  whose invited speakers included Ray Solomonoff, (Turing Award winner and fellow artificial intelligence pioneer) Marvin Minsky, Jorma Rissanen (of Minimum Description Length [MDL]) and (prominent machine learning researcher) J. Ross Quinlan. The contributions sought for this Solomonoff 85th memorial conference are the abovementioned themes and/or anything (else) directly or at least indirectly comparing with or building upon Solomonoff's work. This interdisciplinary conference will be held in Melbourne, Australia. The conference will run for three days, from Wedn 30 November 2011 to Friday 2 December 2011, but might possibly be preceded by a day or halfday of workshops and/or tutorials on Tues 29 November 2011. Conference proceedings will be fullyrefereed and published with a suitable prestigious publisher. Selected papers on suitable topics might be chosen to be expanded upon for journal special issues. Program Committee: Andrew Barron, Statistics, Yale Univ, U.S.A. Greg Chaitin, IBM T.J. Watson Research, U.S.A. Fouad Chedid, Notre Dame Univ, Lebanon Bertrand Clarke, Medical Statistics, Univ Miami, U.S.A. A. Phil Dawid, Statistics, Cambridge University, U.K. David Dowe (Conference and Program chair), Monash Univ Peter Gacs, Boston University, U.S.A. Alex Gammerman, Royal Holloway Univ London, England John Goldsmith, Linguistics, Univ Chicago, U.S.A. Marcus Hutter, Australian National Univ (ANU) Leonid Levin, Boston University, U.S.A. Ming Li, Mathematics, U Waterloo, Canada Marvin Minsky (Turing Award winner), MIT, U.S.A. Kee Siong Ng, ANU (Australia) & EMC Corp Juergen Schmidhuber, IDSIA, Switzerland Farshid Vahid, Econometrics, Monash Univ, Australia Paul Vitanyi, CWI, Amsterdam, Holland Vladimir Vovk, Royal Holloway Univ London, England www.Solomonoff85thMemorial.monash.edu.au Submission deadline: 20 May 2011 Conference dates: Tues 29/Nov/2011  Fri 2/Dec/2011 
