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Math/CS Chat - Thursday, November 29th @ Noon in Rector Lecture Room

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Dr. Greg Wilder will present "Computational Creativity: Teaching Computers to Listen" at the next Math/CS Chat scheduled for Noon on Thursday, November 29th at the Rector Lecture Room. Free pizza & everyone welcome to attend.

Dr. Wilder will discuss factors that make musical data mining unique and describe an autonomous system that overcomes present challenges through the application of research in music cognition as a ground plan for intelligently adaptive algorithms.  His presentation will also relate his experiences bringing those innovations to the music industry and layout a vision for future exploration in the field of computational creativity.

ACM Mid-Atlantic Regional Programming Contest

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Congratulations to the Dickinson College team of Sam Kelly, Qi Wang, and Danfei Xu! They put in a creditable performance at the ACM Mid-Atlantic regional programming contest.  They solved one problem completely and made good attempts at one or two others, placing 91st out of 156 teams.  Full results are at

http://icpc.baylor.edu/public/standings/1376

 

Math/CS Chat - Tuesday, November 13th @ Noon in Tome 115

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Join us on Tuesday, November 13th at Noon in Tome 115 for our next Math/CS Chat.  Chandra Erdman will present "Predicting Response Propensities and Setting Response Rate Expectations in Large National Surveys".  Free pizza and everyone is welcome to attend.

Abstract: The U.S. Census Bureau’s national surveys include the American Community Survey, the Current Population Survey, the Consumer Expenditure Survey, the Survey of Income and Program Participation, the National Health Interview Survey, and the National Crime and Victimization Survey. It is evident from their names that these surveys are diverse in content and level of privacy, and this leads to variation in response rates. Given increasing cost and other resource constraints, there is a clear need to have a good understanding of expected response rate variation that may affect decisions on data collection efforts.  Understanding this variation can be useful in determining when additional field effort on a case may not be cost-effective and in setting realistic interviewer performance expectations.  This talk presents the statistical techniques used by the U.S. Census Bureau in predicting survey case response propensities and in classifying small areas into strata to establish performance expectations for interviewers.