|제목||[학술세미나] [학과세미나] 6월 1일(금) 15시 특별세미나 안내|
|내용||[학과세미나] 6월 1일(금) 15시 특별세미나 안내
▪ 제목 : Belief and random set theory: past, present and future
▪ 연사 : Fabio Cuzzolin (Oxford Brookes University)
▪ 일시 : 2018년 6월 1일(금) PM 15:00 – 18:00
▪ 장소 : 25동 405호
The theory of belief functions, sometimes referred to as evidence theory or Dempster-Shafer theory, was first introduced by Arthur P. Dempster in the context of statistical inference, to be later developed by Glenn Shafer as a general framework for modelling epistemic uncertainty. Belief theory and the closely related random set theory form natural frameworks for modelling situations in which data are missing or scarce: think of extremely rare events such as volcanic eruptions or power plant meltdowns, problems subject to huge uncertainties due to the number and complexity of the factors involved (e.g. climate change), but also the all-important issue with generalisation from small training sets in machine learning.
This tutorial is designed to introduce the principles and rationale of random sets and belief function theory to mainstream statisticians, mathematicians and working scientists, survey the key elements of the methodology and the most recent developments, make practitioners aware of the set of tools that have been developed for reasoning in the belief function framework on real-world problems. Attendees will acquire first-hand knowledge of how to apply these tools to significant problems in major application fields such as computer vision, climate change, and others. A research programme for the future of random set theory and high impact applications is eventually outlined.
세미나 안내_180601_Fabio Cuzzolin.hwp [14.5KB]