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Registration for the 44th Scottish and Northumbrian Academic Statisticians' Meeting is now OPEN at https://www.dur.ac.uk/mathematical.sciences/stats/snasm/ The meeting will take place in the Department of Mathematical Sciences at Durham University on Friday 22nd May 2015. Confirmed speakers are David Wooff (Durham University): Statistical management of pay-per-click processes for search engines Nick Sofroniou (University of Warwick) Random effects models for comparative skills analysis David Banks (Duke University) Text Mining of Document Networks The registration fee is £40 (when registering by March 31 -- note this is earlier than announced previously) which includes coffee and lunch. Reduced rates are available for students. The meeting is of course open to everyone (also beyond Scotland and Northumbria). Additionally, Prof. David Banks will give a short course on May 21 on Data Mining and machine learning (see further details below). Attendance of this short course will be free for registered attendees of the S&N. If you have any questions, please contact Dr Jonathan Cumming, [log in to unmask] Kind regards, The 2015 S&N Organizers ============================================================== Details on the short course on May 21: Title: Data Mining and Machine Learning Instructor: David Banks, Professor, Dept. of Statistical Science, Duke University Date/Time: Thursday, 21th May 2015, 10.30 to 17.00 at Durham University Fees: FREE for all registered attendees of S&N 2015. £10 (contribution to catering) otherwise. Scope: Modern Machine Learning with an applications perspective, especially with examples from text mining and business analytics. Topics include nonparametric regression, the Curse of Dimensionality, the bootstrap, cross-validation, variable selection in the context of L^0, L^1, and L^2 norms, wavelets, nonparametric classification (boosting, bagging, stacking, Random Forests, Support Vector Machines), Latent Dirichlet Allocation for text mining, and, if time permits, cluster analysis and multidimensional scaling. Background Needed: A mid-level knowledge of regression, an introductory course in statistical inference, and it helps to be familiar with a statistical package, such as SAS or R. Target Audience: The course is particularly aimed at postgraduate students in statistics and related fields. We would expect the participants to be M.S. statisticians or people with comparable backgrounds in computer science or math or some fields of engineering. If you have a Ph.D. in statistics, some of the content will be familiar already. Bio: David Banks is a professor in the Department of Statistical Science at Duke University. He obtained his Ph.D. from Virginia Tech in 1984, then did two-year postdoctoral research fellowship with David Blackwell at the University of California at Berkeley. He spent a year as a visiting assistant lecturer at the University of Cambridge before joining the Department of Statistics at Carnegie Mellon. In 1997 he left Carnegie Mellon for the federal government, and worked in three agencies: the National Institute of Standards and Technology, the Department of Transportation, and the Food and Drug Administration. In 2003 he returned to academics at Duke University. You may leave the list at any time by sending the command SIGNOFF allstat to [log in to unmask], leaving the subject line blank.