BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Talks.cam//talks.cam.ac.uk//
X-WR-CALNAME:Talks.cam
BEGIN:VEVENT
SUMMARY:Analysis of metrics for large graphs via approximate Bayesian comp
 utation with application in higher order graphs - Damien Fay (University C
 ollege Cork)
DTSTART:20121214T160000Z
DTEND:20121214T170000Z
UID:TALK41697@talks.cam.ac.uk
CONTACT:Eiko Yoneki
DESCRIPTION:Approximate Bayesian Computation (ABC) is a parameter estimati
 on technique that has become popular recently due to it applicability to s
 ituations in which direct estimation of the likelihood of parameters given
  the data is not possible or problematic. My talk will introduce some new 
 material on the application of ABC to synthetic graphs and models for ther
 mal flow in buildings. In particular ABC provides an estimate of the poste
 rior probability of the parameters given a target.\n\nThe first part of th
 e talk will detail ABC (partly given in tutorial style for those intereste
 d in trying this themselves).\nI shall then detail how this can be applied
  in building energy models together with particle filtering.\nThe second p
 art will start with a comparison of 6 graph metrics via ABC in the case wh
 en the target graph is already known. In particular we show that one of th
 e metrics is seriously flawed while the others demonstrate a trade-off bet
 ween bias and variance in the parameter estimates. The first contribution 
 is the method itself which can be applied to any graph topology generator.
 \n\nIn the second part of the talk we present results on a target graph\, 
 the underlying mechanism of which\, is not known\; the full yeast graph is
  used as an example. We show that the BA topology generator* cannot genera
 te graphs close to this target but still the ABC algorithm identifies thos
 e parameters which are closest (wrt a given metric).\nMuch of the material
  in this talk is novel and represents ongoing research and so for us the a
 im is to get feedback and suggestions for future work.\n\n* Its normally c
 alled the AB generator but here we opt to swap the names to avoid confusio
 n with ABC.\n\nDamien Fay obtained a B.Eng from University College Dublin 
 (1995)\, an MEng (1997) and PhD (2003) from Dublin City University and wor
 ked as a statistics lecturer at the National University of Ireland (2003-2
 007) before joining the NetOS group\, Computer Laboratory\, Cambridge from
 \n2007 and again in 2010. He is currently a research fellow in UCC\, Irela
 nd. His skills lie in the application of statistics to computer networks\,
  social networks and energy systems. His research interests include applie
 d graph theory\, time series analysis and statistical modelling\,\n
LOCATION:FW26\, Computer Laboratory\, William Gates Builiding
END:VEVENT
END:VCALENDAR