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DTSTART;TZID=America/Los_Angeles:20181105T161500
DTEND;TZID=America/Los_Angeles:20181105T171500
DTSTAMP:20260507T233420
CREATED:20180808T152839Z
LAST-MODIFIED:20181021T054250Z
UID:416-1541434500-1541438100@colleges.claremont.edu
SUMMARY:CFTP: the algorithm ERGM deserves\, but not the one it needs right now (Matt Moores\, University of Wollongong)
DESCRIPTION:The exchange algorithm enables Bayesian posterior inference for models with intractable likelihoods\, such as Ising\, Potts\, or exponential random graph models (ERGM). Crucially\, this algorithm relies on an auxiliary Markov chain to obtain an unbiased sample from the generative distribution of the model.             It was originally proposed to use coupling from the past (CFTP) for this purpose\, but this requires the Markov chain to be uniformly ergodic. In the case of the Ising model\, coupling time increases super-exponentially for parameter values larger than the critical point. Alternatives to CFTP\, such as perfect slice sampling or bounding chains for Swendsen-Wang\, have been proposed for the Ising model. However\, there are currently no suitable alternatives for ERGM\, which also features a phase transition that can cause problems with convergence. This talk will review some recent work on simulation algorithms for ERGM and discuss how this problem might be addressed.\n\nThis is joint work with Kerrie Mengersen and Chris Drovandi (QUT\, Australia)\, Antonietta Mira (USI Lugano\, Switzerland)\, and Alberto Caimo (Dublin Inst. Tech.\, Ireland).
URL:https://colleges.claremont.edu/ccms/event/applied-math-seminar-talk-title-tba/
LOCATION:Emmy Noether Room\, Millikan 1021\, Pomona College\, 610 N. College Ave.\, Claremont\, California\, 91711
CATEGORIES:Applied Math Seminar
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DTSTART;TZID=America/Los_Angeles:20181106T121500
DTEND;TZID=America/Los_Angeles:20181106T131000
DTSTAMP:20260507T233420
CREATED:20180911T214141Z
LAST-MODIFIED:20181102T201125Z
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SUMMARY:Turning probability into polynomials (Mark Huber\, CMC)
DESCRIPTION:Moment generating functions (Laplace transforms) are a means for transforming probability problems into problems involving polynomials.  Here I will concentrate on the binomial distribution\, and use the mgf to link this distributions probabilities directly to the binomial theorem.  The mgf is also a key ingredient in Chernoff bounds\, which give upper bounds on the tail probabilities of binomial distributions (aka partial sums of the binomial theorem).  By employing the method of smoothing and tilting\, it is possible to attain bounds on the tails that go down faster than the traditional approximation heuristic that uses the Central Limit Theorem.
URL:https://colleges.claremont.edu/ccms/event/talk-by-mark-huber-cmc/
LOCATION:Millikan 2099\, Pomona College\, 610 N. College Ave.\, Claremont\, CA\, 91711\, United States
CATEGORIES:Algebra / Number Theory / Combinatorics Seminar
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DTSTART;TZID=America/Los_Angeles:20181107T161500
DTEND;TZID=America/Los_Angeles:20181107T171500
DTSTAMP:20260507T233420
CREATED:20180928T171215Z
LAST-MODIFIED:20181102T194937Z
UID:847-1541607300-1541610900@colleges.claremont.edu
SUMMARY:The Legacy of Rudolph Kalman (Andrew Stuart\, Caltech)
DESCRIPTION:Abstract: In 1960 Rudolph Kalman published what is arguably the first paper to develop a systematic\, principled approach to the use of data to improve the predictive capability of mathematical models. As our ability to gather data grows at an enormous rate\,  the importance of this work continues to grow too. The lecture will describe this paper\, and developments that have stemmed from it\, revolutionizing fields such space-craft control\, weather prediction\, oceanography\, oil recovery\, medical imaging and artificial intelligence. Some mathematical details will be also provided\, but limited to simple concepts such as optimization and iteration; the  talk is designed to be broadly accessible to anyone with an  interest in quantitative science.
URL:https://colleges.claremont.edu/ccms/event/andrew-stuart-caltech/
LOCATION:Argue Auditorium\, Pomona College\, 610 N. College Ave.\, Claremont\, CA\, 91711\, United States
CATEGORIES:Colloquium
ORGANIZER;CN="Ali Nadim":MAILTO:ali.nadim@cgu.edu
GEO:34.0999157;-117.7142668
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DTSTART;TZID=America/Los_Angeles:20181108T161500
DTEND;TZID=America/Los_Angeles:20181108T171500
DTSTAMP:20260507T233420
CREATED:20181101T220906Z
LAST-MODIFIED:20181102T043346Z
UID:930-1541693700-1541697300@colleges.claremont.edu
SUMMARY:Crossing the Threshold: The Role of Demographic Stochasticity in the Evolution of Cooperation (Tom LoFaro\, Gustavus Adolphus College)
DESCRIPTION:When Charles Darwin began writing “On the Origin of Species” he knew that explaining cooperative behavior in the context of “survival of the fittest” was problematic.  In fact\, this apparent contradiction puzzled ecologists for many years after.  In this talk we will discuss a mathematical model of the evolution of cooperation developed by Doebeli\, Blarer\, and Ackermann that incorporates ideas from game theory into a standard population genetics model.  We will show that if the model is viewed deterministically then cooperative behavior cannot spread from rarity.  However\, if birth rates are stochastic then cooperative behavior might spread.  We will explore why this is so and describe conditions that increase the probability that cooperative behavior will become established.
URL:https://colleges.claremont.edu/ccms/event/crossing-the-threshold-the-role-of-demographic-stochasticity-in-the-evolution-of-cooperation-tom-lofaro-gustavus-adolphus-college/
LOCATION:Shanahan 3465\, Harvey Mudd College\, 301 Platt Blvd.\, Claremont\, CA\, 91711\, United States
CATEGORIES:Applied Math Seminar
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