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SUMMARY:Combining Formal Methods and Machine Learning - Professor Jane Hil
 lston\, University of Edinburgh
DTSTART:20190522T141500Z
DTEND:20190522T170000Z
UID:TALK124831@talks.cam.ac.uk
CONTACT:Stewart Carswell
DESCRIPTION:Quantitative formal methods\, such as stochastic process algeb
 ras\, have been successfully applied in a number of application domains ov
 er the last 20 years. They offer rigorous techniques for asking questions 
 about the dynamic behaviour of systems.  In the last decade more data-driv
 en approaches to system analysis\, based on machine learning have gained p
 rominence.  Yet the two approaches have complementary strengths and weakne
 sses and should not necessarily be thought of as competing.  In this talk 
 I will talk about two pieces of work in which we have sought to combine ma
 chine learning techniques into a formal modelling framework.\n\nBio: Jane 
 Hillston was appointed Professor of Quantitative Modelling in the School o
 f Informatics at the University of Edinburgh in 2006\, having joined the U
 niversity as a Lecturer in Computer Science in 1995.  She is currently the
  Head of School.\n\nJane Hillston’s research is concerned with formal ap
 proaches to modelling dynamic behaviour\, particularly the use of stochast
 ic process algebras for performance modelling and stochastic verification.
   She has developed high-level modelling languages for application domains
  ranging from computer systems\, biological process and collective adaptiv
 e systems. Her PhD dissertation was awarded the BCS/CPHC Distinguished Dis
 sertation award in 1995 and she was the first recipient of the Roger Needh
 am Award in 2005.  She is a member of Academia Europaea and a Fellow of th
 e Royal Society of Edinburgh.  She has published over 100 journal and conf
 erence papers and held several Research Council and European Commission gr
 ants.\n\nProgramme of the day:\n\n* 3.15 pm  Wheeler Lecture in Lecture Th
 eatre 1\n* 5.00 pm  Drinks Reception\n\n"Register for the talk":https://ww
 w.cst.cam.ac.uk/form/wheeler-register
LOCATION:Lecture Theatre 1\, Computer Laboratory
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